Merge pull request #2826 from yahoo/bratseth/remove-ga

Remove code not necessary for Vespa

28 files changed, 0 insertions, 2193 deletions

diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/CaseList.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/CaseList.java
deleted file mode 100644
index 13343029ebc..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/CaseList.java
+++ /dev/null
@@ -1,15 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-import java.util.List;
-
-/**
- * A producer of a list of cases for function training.
- *
- * @author bratseth
- */
-public interface CaseList {
-
-    public List<TrainingSet.Case> cases();
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Evolvable.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Evolvable.java
deleted file mode 100644
index bbd3844d036..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Evolvable.java
+++ /dev/null
@@ -1,26 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-
-import java.util.List;
-
-/**
- * An entity which may evolve over time
- *
- * @author bratseth
- */
-public abstract class Evolvable implements Comparable<Evolvable> {
-
-    public abstract Evolvable makeSuccessor(int memberNumber, List<RankingExpression> genepool, TrainingEnvironment environment);
-
-    public abstract RankingExpression getGenepool();
-
-    @Override
-    public int compareTo(Evolvable other) {
-        return -Double.compare(getFitness(), other.getFitness());
-    }
-
-    public abstract double getFitness();
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Individual.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Individual.java
deleted file mode 100644
index e42636c00b2..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Individual.java
+++ /dev/null
@@ -1,69 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-
-import java.util.Collections;
-import java.util.List;
-
-/**
- * An individual in an evolving population - a genome with a fitness score.
- * Individuals are comparable by decreasing fitness.
- * <p>
- * As we are training ranking expressions, the genome, here, is the ranking expression.
- *
- * @author bratseth
- */
-public class Individual extends Evolvable {
-
-    private final RankingExpression genome;
-    private final TrainingSet trainingSet;
-    private final double fitness;
-
-    public Individual(RankingExpression genome, TrainingSet trainingSet) {
-        this.genome = genome;
-        this.trainingSet = trainingSet;
-        this.fitness = trainingSet.evaluate(genome);
-    }
-
-    public RankingExpression getGenome() { return genome; }
-
-    public double calculateAverageError() {
-        return trainingSet.calculateAverageError(genome);
-    }
-
-    public double calculateAverageErrorPercentage() {
-        return trainingSet.calculateAverageErrorPercentage(genome);
-    }
-
-    @Override
-    public double getFitness() { return fitness; }
-
-    @Override
-    public Individual makeSuccessor(int memberNumber, List<RankingExpression> genepool, TrainingEnvironment environment) {
-        return new Individual(environment.recombiner().recombine(genome, genepool), trainingSet);
-    }
-
-    @Override
-    public RankingExpression getGenepool() {
-        return genome;
-    }
-
-    @Override
-    public String toString() {
-        return toSomewhatShortString() + ", expression: " + genome;
-    }
-
-    /** Returns a shorter string describing this (not including the expression */
-    public String toSomewhatShortString() {
-        return "Error % " + calculateAverageErrorPercentage() +
-                " average error " + calculateAverageError() +
-                " fitness " + getFitness();
-    }
-
-    /** Returns a shorter string describing this (not including the expression */
-    public String toShortString() {
-        return "Error: " + calculateAverageErrorPercentage() + " %";
-    }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/KeyboardChecker.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/KeyboardChecker.java
deleted file mode 100644
index 58e569bef33..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/KeyboardChecker.java
+++ /dev/null
@@ -1,50 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-import java.awt.KeyEventDispatcher;
-import java.awt.KeyboardFocusManager;
-import java.awt.event.KeyEvent;
-
-/**
- * TODO
- *
- * @author bratseth
- */
-public class KeyboardChecker {
-
-    private static boolean qPressed = false;
-
-    private final Object lock = new Object();
-
-    public KeyboardChecker() {
-        KeyboardFocusManager.getCurrentKeyboardFocusManager().addKeyEventDispatcher(new KeyEventDispatcher() {
-
-            @Override
-            public boolean dispatchKeyEvent(KeyEvent ke) {
-                synchronized (lock) {
-                    switch (ke.getID()) {
-                        case KeyEvent.KEY_PRESSED:
-                            if (ke.getKeyCode() == KeyEvent.VK_Q) {
-                                qPressed = true;
-                            }
-                            break;
-
-                        case KeyEvent.KEY_RELEASED:
-                            if (ke.getKeyCode() == KeyEvent.VK_Q) {
-                                qPressed = false;
-                            }
-                            break;
-                    }
-                    return false;
-                }
-            }
-        });
-    }
-
-    public boolean isQPressed() {
-        synchronized (lock) {
-            return qPressed;
-        }
-    }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Main.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Main.java
deleted file mode 100644
index 204c03b92b6..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Main.java
+++ /dev/null
@@ -1,73 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-import com.yahoo.io.IOUtils;
-import com.yahoo.searchlib.mlr.ga.caselist.FileCaseList;
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-import com.yahoo.searchlib.rankingexpression.parser.ParseException;
-
-import java.io.BufferedReader;
-import java.io.FileReader;
-import java.io.IOException;
-
-/**
- * Command line runner for training sessions
- *
- * @author bratseth
- */
-/*
-TODO: Switch order of generation and sequence in names
-TODO: Output fitness improvement on each step (esp useful for species evolution)
-TODO: Detect local optima (no improvement for n rounds) and stop early
-TODO: Split into training and validation sets
- */
-public class Main {
-
-    public Main(String[] args, Tracker tracker) {
-        if (args.length < 1 || args[0].trim().equals("help")) {
-            System.out.println(
-                    "Finds a ranking expression matching a training set given as a case file.\n" +
-                    "Run until the expression seems good enough.\n" +
-                    "Usage: ga <case-file> - \n" +
-                    "    where case-file is a file containing case lines on the form \n" +
-                    "        targetValue, argument1:value1, ...\n" +
-                    "        (comment lines starting by # are also permitted)\n");
-            return;
-        }
-
-        TrainingParameters parameters = new TrainingParameters();
-        //parameters.setAllowConditions(false);
-        parameters.setErrorIsRelative(false);
-        parameters.setInitialSpeciesSize(40);
-        parameters.setSpeciesLifespan(100);
-        parameters.setExcludeFeatures("F7,F9,F10,F11,F12,F13,F14,F15,F16,F17,F18,F19,F21,F23,F24,F25,F26,F27,F29,F30,F32,F33,F34,F35,F36,F37,F38,F39,F40,F41,F42,F44,F46,F47,F48,F49,F50,F52,F53,F55,F56,F57,F58,F59,F60,F61,F62,F63,F64,F65,F67,F69,F70,F71,F72,F73,F75,F76,F78,F79,F80,F81,F82,F83,F84,F85,F86,F87,F88,F90,F92,F93,F94,F95,F96,F98,F99,F100,F101,F102,F103,F104,F105,F106,F107,F108,F109,F66,F89,F110");
-        //parameters.setInitialSpeciesSize(20);
-
-        String caseFile = args[0];
-        TrainingSet trainingSet = new TrainingSet(FileCaseList.create(caseFile, parameters), parameters);
-        Trainer trainer = new Trainer(trainingSet);
-
-        if (args.length > 1) { // Evaluate given expression
-            try {
-                Individual given = new Individual(new RankingExpression(new BufferedReader(new FileReader(args[1]))), trainingSet);
-                System.out.println("Error in '" + args[1] + "': error % " + given.calculateAverageErrorPercentage() +
-                                                              " average error " + given.calculateAverageError() +
-                                                              " fitness " + given.getFitness());
-            }
-            catch (IOException | ParseException e) {
-                throw new IllegalArgumentException("Could not evaluate expression in argument 2", e);
-            }
-        }
-        else { // Train expression
-            // TODO: Move system outs to tracker
-            System.out.println("Learning ...");
-            RankingExpression learntExpression = trainer.train(parameters, tracker);
-            System.out.println("Learnt expression: " + learntExpression);
-        }
-    }
-
-    public static void main(String[] args) {
-        new Main(args, new PrintingTracker(10, 0, 1));
-    }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Population.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Population.java
deleted file mode 100644
index 8aa47db6d09..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Population.java
+++ /dev/null
@@ -1,60 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-
-import java.util.ArrayList;
-import java.util.Collections;
-import java.util.List;
-
-/**
- * A collection of evolvables
- *
- * @author bratseth
- */
-public class Population {
-
-    /** The current members of this population, always sorted by decreasing fitness */
-    private List<Evolvable> members;
-
-    public Population(List<Evolvable> initialMembers) {
-        members = new ArrayList<>(initialMembers);
-        Collections.sort(members);
-    }
-
-    /** Returns the most fit member of this population (never null) */
-    public Evolvable best() {
-        return members.get(0);
-    }
-
-    /** Returns the members of this population as an unmodifiable list sorted by decreasing fitness*/
-    public List<Evolvable> members() { return Collections.unmodifiableList(members); }
-
-    public void evolve(int generation, TrainingEnvironment environment) {
-        TrainingParameters p = environment.parameters();
-        int generationSize = p.getInitialSpeciesSize() -
-                             (int)Math.round((p.getInitialSpeciesSize() - p.getFinalSpeciesSize()) * generation/p.getSpeciesLifespan());
-        members = breed(members, generationSize * p.getGenerationCandidatesFactor(), environment);
-        Collections.sort(members);
-        members = members.subList(0, Math.min(generationSize, members.size()));
-    }
-
-    private List<Evolvable> breed(List<Evolvable> members, int offspringCount, TrainingEnvironment environment) {
-        List<Evolvable> offspring = new ArrayList<>(offspringCount); // TODO: Can we do this inline and keep the list forever (and then also the immutable view)
-        offspring.add(members.get(0)); // keep the best as-is
-        List<RankingExpression> genePool = collectGenepool(members);
-        for (int i = 0; i < offspringCount - 1; i++) {
-            Evolvable child = members.get(i % members.size()).makeSuccessor(i, genePool, environment);
-            offspring.add(child);
-        }
-        return offspring;
-    }
-
-    private List<RankingExpression> collectGenepool(List<Evolvable> members) {
-        List<RankingExpression> genepool = new ArrayList<>();
-        for (Evolvable member : members)
-            genepool.add(member.getGenepool());
-        return genepool;
-    }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/PrintingTracker.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/PrintingTracker.java
deleted file mode 100644
index 1bd7980bc3f..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/PrintingTracker.java
+++ /dev/null
@@ -1,91 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-import com.yahoo.yolean.Exceptions;
-
-import java.util.List;
-
-/**
- * A tracker which prints a summary of training events to standard out
- *
- * @author bratseth
- */
-public class PrintingTracker implements Tracker {
-
-    private final int iterationEvery;
-    private final int survivorsEvery;
-    private final int printSpeciesCreationLevel;
-    private final int printSpeciesCompletionLevel;
-
-    public PrintingTracker() {
-        this(0, 1);
-    }
-
-    public PrintingTracker(int printSpeciesCreationLevel, int printSpeciesCompletionLevel) {
-        this(Integer.MAX_VALUE, Integer.MAX_VALUE, printSpeciesCreationLevel, printSpeciesCompletionLevel);
-    }
-
-    public PrintingTracker(int iterationEvery, int printSpeciesCreationLevel, int printSpeciesCompletionLevel) {
-        this(iterationEvery, Integer.MAX_VALUE, printSpeciesCreationLevel, printSpeciesCompletionLevel);
-    }
-
-    public PrintingTracker(int iterationEvery, int survivorsEvery, int printSpeciesCreationLevel, int printSpeciesCompletionLevel) {
-        this.iterationEvery = iterationEvery;
-        this.survivorsEvery = survivorsEvery;
-        this.printSpeciesCreationLevel = printSpeciesCreationLevel;
-        this.printSpeciesCompletionLevel = printSpeciesCompletionLevel;
-    }
-
-    @Override
-    public void newSpecies(Species predecessor, int initialSize, List<RankingExpression> genePool) {
-        if (predecessor.name().level() > printSpeciesCreationLevel) return;
-        System.out.println(spaces(predecessor.name().level()*2) +  "Creating new species of size " + initialSize + " and a gene pool of size " + genePool.size() + " from predecessor " + predecessor);
-    }
-
-    @Override
-    public void newSpeciesCreated(Species species) {
-        if (species.name().level() > printSpeciesCreationLevel) return;
-        System.out.println(spaces(species.name().level()*2) +  "Created and will now evolve " + species);
-    }
-
-    @Override
-    public void speciesCompleted(Species species) {
-        if (species.name().level() > printSpeciesCompletionLevel) return;
-        System.out.println(spaces(species.name().level()*2) +  "--> Evolution completed for " + species);
-    }
-
-    /** Called each time a species (or super-species) have completed one generation */
-    @Override
-    public void iteration(Species species, int generation) {
-        try {
-            new RankingExpression(species.bestIndividual().getGenome().toString());
-        }
-        catch (Exception e) {
-            System.err.println("ERROR: " + Exceptions.toMessageString(e) + ": " + species.bestIndividual().getGenome());
-        }
-
-        if ( (generation % iterationEvery) == 0)
-            System.out.println(spaces(species.name().level()*2) +  "Gen " + generation + " of " + species);
-
-        if ( (generation % survivorsEvery) == 0)
-            printPopulation(species.name().level(), species.population().members());
-    }
-
-    @Override
-    public void result(Evolvable winner) {
-        System.out.println("Learnt expression: " + winner);
-    }
-
-    private String spaces(int spaces) {
-        return "                             ".substring(0,spaces);
-    }
-
-    private void printPopulation(int level, List<Evolvable> survivors) {
-        if (survivors.size()<=1) return;
-        System.out.println("    Population:");
-        for (Evolvable individual : survivors)
-            System.out.println(spaces(level*2) + "    " + individual);
-    }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/RankingExpressionCaseList.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/RankingExpressionCaseList.java
deleted file mode 100644
index 596db4cfd42..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/RankingExpressionCaseList.java
+++ /dev/null
@@ -1,33 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-import com.yahoo.searchlib.mlr.ga.CaseList;
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-import com.yahoo.searchlib.rankingexpression.evaluation.Context;
-import com.yahoo.searchlib.mlr.ga.TrainingSet;
-
-import java.util.ArrayList;
-import java.util.Collections;
-import java.util.List;
-
-/**
- * Produces a list of training cases (argument and target value pairs)
- * from a Ranking Expression.
- * Useful for testing.
- *
- * @author bratseth
- */
-public class RankingExpressionCaseList implements CaseList {
-
-    private final List<TrainingSet.Case> cases = new ArrayList<TrainingSet.Case>();
-
-    public RankingExpressionCaseList(List<Context> arguments, RankingExpression targetFunction) {
-        for (Context argument : arguments)
-            cases.add(new TrainingSet.Case(argument,targetFunction.evaluate(argument).asDouble()));
-    }
-
-    /** Returns the list of cases generated from the ranking expression */
-    @Override
-    public List<TrainingSet.Case> cases() { return Collections.unmodifiableList(cases); }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Recombiner.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Recombiner.java
deleted file mode 100644
index 8fd40ec793f..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Recombiner.java
+++ /dev/null
@@ -1,200 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-import com.yahoo.searchlib.rankingexpression.evaluation.DoubleValue;
-import com.yahoo.searchlib.rankingexpression.rule.*;
-
-import java.util.*;
-import java.util.logging.Logger;
-
-import static java.lang.Math.abs;
-import static java.lang.Math.max;
-import static java.lang.Math.min;
-
-/**
- * A class which returns a mutated, recombined genome from a list of parent genomes.
- *
- * @author bratseth
- */
-public class Recombiner {
-
-    // TODO: Either make ranking expressions immutable and get rid of parent pointer, or do clone everywhere below
-
-    private static final Logger log = Logger.getLogger(Trainer.class.getName());
-
-    private final Random random = new Random();
-
-    private final List<String> features;
-
-    private final TrainingParameters parameters;
-
-    /**
-     * Creates a recombiner
-     *
-     * @param features the list of feature names which are possible within the space we are training,
-     *                 such that these may be spontaneously added to expressions.
-     */
-    public Recombiner(Collection<String> features, TrainingParameters trainingParameters) {
-        this.features = Collections.unmodifiableList(new ArrayList<>(features));
-        this.parameters = trainingParameters;
-    }
-
-    public RankingExpression recombine(RankingExpression genome, List<RankingExpression> genePool) {
-        List<ExpressionNode> genePoolRoots = new ArrayList<>();
-        for (RankingExpression genePoolGenome : genePool)
-            genePoolRoots.add(genePoolGenome.getRoot());
-        return new RankingExpression(mutate(genome.getRoot(), genePoolRoots, 0));
-    }
-
-    private ExpressionNode mutate(ExpressionNode gene, List<ExpressionNode> genePool, int depth) {
-        // TODO: Extract insert level
-        if (gene instanceof BooleanNode)
-            return simplifyCondition(mutateChildren((CompositeNode)gene,genePool,depth+1));
-        if (gene instanceof CompositeNode)
-            return insertNodeLevel(simplify(removeNodeLevel(mutateChildren((CompositeNode)gene,genePool,depth+1))), genePool, depth+1);
-        else
-            return insertNodeLevel(mutateLeaf(gene), genePool, depth+1);
-    }
-
-    private BooleanNode simplifyCondition(ExpressionNode node) {
-        // Nothing yet
-        return (BooleanNode)node;
-    }
-
-    /** Very basic algorithmic simplification */
-    private ExpressionNode simplify(ExpressionNode node) {
-        if (! (node instanceof CompositeNode)) return node;
-        CompositeNode composite = (CompositeNode)node;
-        if (maxDepth(composite)>2) return composite;
-        List<ExpressionNode> children = composite.children();
-        if (children.size()!=2) return composite;
-        if ( ! (children.get(0) instanceof ConstantNode)) return composite;
-        if ( ! (children.get(1) instanceof ConstantNode)) return composite;
-        return new ConstantNode(composite.evaluate(null));
-    }
-
-    private CompositeNode mutateChildren(CompositeNode gene, List<ExpressionNode> genePool, int depth) {
-        if (gene instanceof ReferenceNode) return gene; // TODO: Remove if we make this a non-composite
-
-        List<ExpressionNode> mutatedChildren = new ArrayList<>();
-        for (ExpressionNode child : gene.children())
-            mutatedChildren.add(mutate(child, genePool, depth));
-        return gene.setChildren(mutatedChildren);
-    }
-
-    private ExpressionNode insertNodeLevel(ExpressionNode gene, List<ExpressionNode> genePool, int depth) {
-        if (probability() < 0.9) return gene;
-        if (depth + maxDepth(gene) >= parameters.getMaxExpressionDepth()) return gene;
-        ExpressionNode newChild = generateChild(genePool, depth);
-        if (probability() < 0.5)
-            return generateComposite(gene, newChild, genePool, depth);
-        else
-            return generateComposite(newChild, gene, genePool, depth);
-    }
-
-    private ExpressionNode removeNodeLevel(CompositeNode gene) {
-        if (gene instanceof ReferenceNode) return gene; // TODO: Remove if we make featurenode a non-composite
-        if (probability() < 0.9) return gene;
-        return randomFrom(gene.children());
-    }
-
-    private ExpressionNode generateComposite(ExpressionNode left, ExpressionNode right, List<ExpressionNode> genePool, int depth) {
-        int type = random.nextInt(2 + ( parameters.getAllowConditions() ? 1:0 ) ); // pick equally between 2 or 3 types
-        if (type == 0) {
-            return new ArithmeticNode(left, pickArithmeticOperator(), right);
-        }
-        else if (type == 1) {
-            Function function = pickFunction();
-            if (function.arity() == 1)
-                return new FunctionNode(function, left);
-            else // arity==2
-                return new FunctionNode(function, left, right);
-        }
-        else {
-            return new IfNode(generateCondition(genePool, depth + 1), left, right);
-        }
-    }
-
-    private BooleanNode generateCondition(List<ExpressionNode> genePool, int depth) {
-        // TODO: Add set membership nodes
-        return new ComparisonNode(generateChild(genePool, depth), TruthOperator.SMALLER, generateChild(genePool, depth));
-    }
-
-    private ExpressionNode generateChild(List<ExpressionNode> genePool, int depth) {
-        if (genePool.isEmpty() || probability() < 0.1) { // entirely new child
-            return generateLeaf();
-        }
-        else { // pick from gene pool
-            ExpressionNode picked = randomFrom(genePool);
-            int pickedDepth = 0;
-            // descend until we are at at least the same depth as this depth
-            // to make sure branches spliced in are shallow enough that we avoid growing
-            // larger than maxDepth
-            while (picked instanceof CompositeNode && (pickedDepth++ < depth || probability() < 0.5)) {
-                if (picked instanceof ReferenceNode) continue; // TODO: Remove if we make referencenode a noncomposite
-                picked = randomFrom(((CompositeNode)picked).children());
-            }
-            return picked;
-        }
-    }
-
-    public ExpressionNode mutateLeaf(ExpressionNode leaf) {
-        if (probability() < 0.5) return leaf; // TODO: For performance. Drop?
-        // TODO: Other leaves
-        ConstantNode constant = (ConstantNode)leaf;
-        return new ConstantNode(DoubleValue.frozen(constant.getValue().asDouble()*aboutOne()));
-    }
-
-    public ExpressionNode generateLeaf() {
-        if (probability()<0.5 || features.size() == 0)
-            return new ConstantNode(DoubleValue.frozen(random.nextDouble() * 2000 - 1000)); // TODO: Use some non-uniform distribution
-        else
-            return new ReferenceNode(randomFrom(features));
-    }
-
-    private double aboutOne() {
-        return 1 + Math.pow(-0.1, random.nextInt(4) + 1);
-    }
-
-    private double probability() {
-        return random.nextDouble();
-    }
-
-    private <T> T randomFrom(List<T> expressionList) {
-        return expressionList.get(random.nextInt(expressionList.size()));
-    }
-
-    private ArithmeticOperator pickArithmeticOperator() {
-        switch (random.nextInt(4)) {
-            case 0: return ArithmeticOperator.PLUS;
-            case 1: return ArithmeticOperator.MINUS;
-            case 2: return ArithmeticOperator.MULTIPLY;
-            case 3: return ArithmeticOperator.DIVIDE;
-        }
-        throw new RuntimeException("This cannot happen");
-    }
-
-    /** Pick among the subset of functions which are probably useful */
-    private Function pickFunction() {
-        switch (random.nextInt(5)) {
-            case 0: return Function.tanh;
-            case 1: return Function.exp;
-            case 2: return Function.log;
-            case 3: return Function.pow;
-            case 4: return Function.sqrt;
-        }
-        throw new RuntimeException("This cannot happen");
-    }
-
-    // TODO: Make ranking expressions immutable and compute this on creation?
-    private int maxDepth(ExpressionNode node) {
-        if ( ! (node instanceof CompositeNode)) return 1;
-
-        int maxChildDepth = 0;
-        for (ExpressionNode child : ((CompositeNode)node).children())
-            maxChildDepth = Math.max(maxDepth(child), maxChildDepth);
-        return maxChildDepth + 1;
-    }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Species.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Species.java
deleted file mode 100644
index 1870f9c0afc..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Species.java
+++ /dev/null
@@ -1,93 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-
-import java.util.ArrayList;
-import java.util.List;
-
-/**
- * A species is a population of evolvables.
- * Contrary to a real species, a species population may contain (sub)species
- * rather than individuals - at all levels but the lowest.
- *
- * @author bratseth
- */
-public class Species extends Evolvable {
-
-    private SpeciesName name;
-    private final Population population;
-
-    /** Create a species having a given initial population */
-    public Species(SpeciesName name, Population population) {
-        this.name = name;
-        this.population = population;
-    }
-
-    /** Create a species evolved from a predecessor species, using the given gene pool for mutating it */
-    private Species(SpeciesName name, Species predecessor, List<RankingExpression> genepool, TrainingEnvironment environment) {
-        this.name = name;
-        environment.tracker().newSpecies(predecessor, environment.parameters().getInitialSpeciesSize(), genepool);
-
-        // Initialize new species with members generated from the predecessor species
-        List<Evolvable> initialMembers = new ArrayList<>();
-        for (int i = 0; i < environment.parameters().getInitialSpeciesSize(); i++)
-            initialMembers.add(drawFrom(predecessor.population, i).makeSuccessor(i, genepool, environment));
-        population = new Population(initialMembers);
-
-        // Evolve the population of this species for the configured number of generations
-        environment.tracker().newSpeciesCreated(this);
-        for (int generation = 0; generation < environment.parameters().getSpeciesLifespan(); generation++) {
-            environment.tracker().iteration(this, generation+1);
-            population.evolve(generation, environment);
-            if (Double.isInfinite(bestIndividual().getFitness())) break; // jackpot
-            // if (keyboardChecker.isQPressed()) break; // user quit TODO: Make work
-        }
-        environment.tracker().speciesCompleted(this);
-    }
-
-    /**
-     * Draws a member from the given population, where the probability of being drawn is proportional to the
-     * fitness of the member
-     */
-    private Evolvable drawFrom(Population population, int succession) {
-        return population.members().get(Math.min(succession % 3, population.members().size() - 1)); // TODO: Probabilistic by fitness?
-    }
-
-    public SpeciesName name() { return name; }
-
-    /** The fitness of the fittest individual in the population */
-    @Override
-    public double getFitness() {
-        return population.best().getFitness();
-    }
-
-    /** Creates the successor of this, using its genes, mutated drawing from the given gene pool */
-    @Override
-    public Evolvable makeSuccessor(int memberNumber, List<RankingExpression> genepool, TrainingEnvironment environment) {
-        return new Species(name.successor(memberNumber), this, genepool, environment);
-    }
-
-    /** Returns the members of this species */
-    public Population population() { return population; }
-
-    /** The genes of the fittest individual in the population of this */
-    @Override
-    public RankingExpression getGenepool() { // TODO: Less sharp?
-        return population.best().getGenepool();
-    }
-
-    /** Returns the best individual below this in the species hierarchy (e.g recursively the best leaf) */
-    public Individual bestIndividual() {
-        Evolvable child = this;
-        while (child instanceof Species)
-            child = ((Species)child).population.best();
-        return (Individual)child; // it is when it is not instanceof Species
-    }
-
-    @Override
-    public String toString() {
-        return "species " + name + ", best member: " + population.best();
-    }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/SpeciesName.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/SpeciesName.java
deleted file mode 100644
index 862d8e8899d..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/SpeciesName.java
+++ /dev/null
@@ -1,54 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-/**
- * The name of a species. For tracking purposes.
- * A name has the form superSpeciesName + "/" + serialNumber.generationNumber.
- *
- * @author bratseth
- */
-public class SpeciesName {
-
-    private final int level, serial, generation;
-
-    private final String name, prefixName;
-
-    private SpeciesName(int level, int serial, int generation, String prefixName) {
-        this.level = level;
-        this.serial = serial;
-        this.generation = generation;
-        this.prefixName = prefixName;
-        if (level == 0)
-            this.name = "";
-        else
-            this.name = prefixName + (prefixName.isEmpty() ? "" : "/") + serial + "." + generation;
-    }
-
-    /**
-     * The level in the species hierarchy of the species having this name.
-     * The root species has level 0.
-     */
-    public int level() { return level; }
-
-    /** Returns the name of the root species: The empty string at level 0 */
-    public static SpeciesName createRoot() {
-        return new SpeciesName(0 ,0 ,0, "");
-    }
-
-    @Override
-    public String toString() {
-        if (level == 0) return "(root)";
-        return name;
-    }
-
-    /** Returns the name of a new subspecies */
-    public SpeciesName subspecies(int serial) {
-        return new SpeciesName(level+1, serial, 0, name);
-    }
-
-    /** Returns the name of the successor of this species */
-    public SpeciesName successor(int serial) {
-        return new SpeciesName(level, serial, generation+1, prefixName);
-    }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Tracker.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Tracker.java
deleted file mode 100644
index 0a18820560b..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Tracker.java
+++ /dev/null
@@ -1,25 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-
-import java.util.List;
-
-/**
- * A tracker receives callbacks about events happening during a training session.
- *
- * @author bratseth
- */
-public interface Tracker {
-
-    public void newSpecies(Species predecessor, int initialSize, List<RankingExpression> genePool);
-
-    public void newSpeciesCreated(Species species);
-
-    public void speciesCompleted(Species species);
-
-    public void iteration(Species species, int generation);
-
-    public void result(Evolvable winner);
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Trainer.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Trainer.java
deleted file mode 100644
index b5268f1bb98..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/Trainer.java
+++ /dev/null
@@ -1,57 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-import com.yahoo.searchlib.rankingexpression.evaluation.DoubleValue;
-import com.yahoo.searchlib.rankingexpression.parser.ParseException;
-import com.yahoo.searchlib.rankingexpression.rule.ConstantNode;
-
-import java.util.ArrayList;
-import java.util.Arrays;
-import java.util.Collection;
-import java.util.Collections;
-import java.util.HashSet;
-import java.util.List;
-import java.util.Set;
-
-/**
- * Learns a ranking expression from some seed expressions and a training set.
- *
- * @author bratseth
- */
-public class Trainer {
-
-    // TODO: Simplify this to constructor only ... or maybe remove ... or combine with TrainingEnvironment
-    // TODO: Also: Rename to Training?
-
-    private final TrainingSet trainingSet;
-    private final Set<String> argumentNames;
-
-    /**
-     * Creates a new trainer.
-     */
-    public Trainer(TrainingSet trainingSet) {
-        this(trainingSet, trainingSet.argumentNames());
-    }
-
-    /**
-     * Creates a new trainer which uses a specified list of expression argument names
-     * rather than the argument names given by the training set.
-     */
-    public Trainer(TrainingSet trainingSet, Set<String> argumentNames) {
-        this.trainingSet = trainingSet;
-        this.argumentNames = new HashSet<>(argumentNames);
-    }
-
-    public RankingExpression train(TrainingParameters parameters, Tracker tracker) {
-        TrainingEnvironment environment = new TrainingEnvironment(new Recombiner(argumentNames, parameters), tracker, trainingSet, parameters);
-        SpeciesName rootName = SpeciesName.createRoot();
-        Species genesisSubSpecies = new Species(rootName.subspecies(0), new Population(Collections.<Evolvable>singletonList(new Individual(new RankingExpression(new ConstantNode(new DoubleValue(1))), trainingSet))));
-        Species rootSpecies = (Species) new Species(rootName, new Population(Collections.<Evolvable>singletonList(genesisSubSpecies)))
-                              .makeSuccessor(0, Collections.<RankingExpression>emptyList(), environment);
-        Individual winner = rootSpecies.bestIndividual();
-        tracker.result(winner);
-        return winner.getGenome();
-    }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/TrainingEnvironment.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/TrainingEnvironment.java
deleted file mode 100644
index e874267970c..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/TrainingEnvironment.java
+++ /dev/null
@@ -1,31 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-/**
- * The static environment of a training session
- *
- * @author bratseth
- */
-public class TrainingEnvironment {
-
-    // TODO: Not sure if this belongs ... or should even be an instance
-    // TODO: maybe collapse Trainer into this and call it TrainingSession
-    private final Recombiner recombiner;
-    private final Tracker tracker;
-    private final TrainingSet trainingSet;
-    private final TrainingParameters parameters;
-
-    public TrainingEnvironment(Recombiner recombiner, Tracker tracker,
-                               TrainingSet trainingSet, TrainingParameters parameters) {
-        this.recombiner = recombiner;
-        this.tracker = tracker;
-        this.trainingSet = trainingSet;
-        this.parameters = parameters;
-    }
-
-    public Recombiner recombiner() { return recombiner; }
-    public Tracker tracker() { return tracker; }
-    public TrainingSet trainingSet() { return trainingSet; }
-    public TrainingParameters parameters() { return parameters; }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/TrainingParameters.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/TrainingParameters.java
deleted file mode 100644
index 71ff8bfe259..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/TrainingParameters.java
+++ /dev/null
@@ -1,100 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-import java.util.HashSet;
-import java.util.Set;
-
-/**
- * @author bratseth
- */
-public class TrainingParameters {
-
-    // A note:
-    // The total number of species generated and evaluated is
-    // (generationCandidatesFactor * speciesLifespan * (initialSpeciesSize-finalSpeciesSize)/2 ) ^ speciesLevels
-    // (speciesLevel is hardcoded to 2 atm)
-
-    private int speciesLifespan = 1000;
-    private int initialSpeciesSize = 10;
-    private double finalSpeciesSize = 1;
-    private int generationCandidatesFactor = 3;
-    private int maxExpressionDepth = 6;
-    private boolean allowConditions = true;
-    private boolean errorIsRelative = true;
-    private Set<String> excludeFeatures = new HashSet<>();
-    private String trainingSetFormat = null;
-    private double validationFraction = 0.2;
-
-    /** The number of generation which a given species (or super-species at any level) lives. Default:1000 */
-    public int getSpeciesLifespan() { return speciesLifespan; }
-    public void setSpeciesLifespan(int generations) { this.speciesLifespan = generations; }
-
-    /** The number of members in a species (or super-species at any level) as it is created. Default: 10 */
-    public int getInitialSpeciesSize() { return initialSpeciesSize; }
-    public void setInitialSpeciesSize(int initialSpeciesSize) { this.initialSpeciesSize = initialSpeciesSize; }
-
-    /**
-     * The number of members in a species in its final generation.
-     * The size of the species will be reduced linearly in each generation to go from initial size to final size.
-     * Default: 1
-     */
-    public double getFinalSpeciesSize() { return finalSpeciesSize; }
-    public void setFinalSpeciesSize(int finalSpeciesSize) { this.finalSpeciesSize = finalSpeciesSize; }
-
-    /*
-     * The factor determining how many more members are generated than are allowed to survive in each generation of a species.
-     * Default: 3
-     */
-    public int getGenerationCandidatesFactor() { return generationCandidatesFactor; }
-    public void setGenerationCandidatesFactor(int generationCandidatesFactor) { this.generationCandidatesFactor = generationCandidatesFactor; }
-
-    /**
-     * The max depth of expressions this is allowed to generate.
-     * Default: 6
-     */
-    public int getMaxExpressionDepth() { return maxExpressionDepth; }
-    public void setMaxExpressionDepth(int maxExpressionDepth) { this.maxExpressionDepth = maxExpressionDepth; }
-
-    /**
-     * Whether mutation should allow creation of condition (if) expressions.
-     * Default: true
-     */
-    public boolean getAllowConditions() { return allowConditions; }
-    public void setAllowConditions(boolean allowConditions) { this.allowConditions = allowConditions; }
-
-    /**
-     * Whether errors are relative to the absolute value of the function at that point or not.
-     * If true, training will assign equal weight to the error of 1.1 for 1 and 110 for 100.
-     * If false, training will instead assign a 10x weight to the latter.
-     * Default: True.
-     */
-    public boolean getErrorIsRelative() { return errorIsRelative; }
-    public void setErrorIsRelative(boolean errorIsRelative) { this.errorIsRelative = errorIsRelative; }
-
-    /**
-     * Returns the set of features to exclude during training.
-     * Returned as an immutable set, never null.
-     */
-    public Set<String> getExcludeFeatures() { return excludeFeatures; }
-    /** Sets the features to exclude from a comma-separated string */
-    public void setExcludeFeatures(String excludeFeatureString) {
-        for (String featureName : excludeFeatureString.split(","))
-            excludeFeatures.add(featureName.trim());
-    }
-
-    /**
-     * Returns the format of the training set to read. "fv" or "cvs" is supported.
-     * If this is null the format name is taken from the last name of the file instead.
-     * Default: null.
-     */
-    public String getTrainingSetFormat() { return trainingSetFormat; }
-    public void setTrainingSetFormat(String trainingSetFormat) { this.trainingSetFormat = trainingSetFormat; }
-
-    /**
-     * Returns the fraction of the result set to hold out of training and use for validation.
-     * Default 0.2
-     */
-    public double getValidationFraction() { return validationFraction; }
-    public void setValidationFraction(double validationFraction) { this.validationFraction = validationFraction; }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/TrainingSet.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/TrainingSet.java
deleted file mode 100644
index f7917987f91..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/TrainingSet.java
+++ /dev/null
@@ -1,122 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga;
-
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-import com.yahoo.searchlib.rankingexpression.evaluation.Context;
-
-import java.util.Collections;
-import java.util.HashSet;
-import java.util.List;
-import java.util.Set;
-
-/**
- * A training set: a set of <i>cases</i>: Input data to output value pairs
- *
- * @author bratseth
- */
-public class TrainingSet {
-
-    private final TrainingParameters parameters;
-    private final List<Case> trainingCases;
-    private final List<Case> validationCases;
-    private final Set<String> argumentNames = new HashSet<>();
-
-    /**
-     * Creates a training set from a list of cases.
-     * The ownership of the argument list and all the cases are transferred to this by this call.
-     */
-    public TrainingSet(CaseList caseList, TrainingParameters parameters) {
-        List<Case> cases = caseList.cases();
-
-        this.parameters = parameters;
-        for (Case aCase : cases)
-            argumentNames.addAll(aCase.arguments().names());
-        argumentNames.removeAll(parameters.getExcludeFeatures());
-
-        int validationCaseCount = (int)Math.round((cases.size() * parameters.getValidationFraction()));
-        this.validationCases = cases.subList(0, validationCaseCount);
-        this.trainingCases = cases.subList(validationCaseCount, cases.size());
-    }
-
-    public Set<String> argumentNames() {
-        return Collections.unmodifiableSet(argumentNames);
-    }
-
-    /**
-     * Returns the fitness of a genome (ranking expression) according to this training set.
-     * The fitness to be returned by this is the inverse of the average squared difference between the
-     * target function result and the function result returned by the genome function.
-     */
-    // TODO: Take expression length into account.
-    public double evaluate(RankingExpression genome) {
-        boolean constantExpressionGenome = true;
-        double squaredErrorSum = 0;
-        Double previousValue = null;
-        for (Case trainingCase : trainingCases) {
-            double value =  genome.evaluate(trainingCase.arguments()).asDouble();
-            double error = saneAbs(effectiveError(trainingCase.targetValue(), value));
-            squaredErrorSum += Math.pow(error, 2);
-
-            if (previousValue != null && previousValue != value)
-                constantExpressionGenome = false;
-            previousValue = value;
-        }
-        if (constantExpressionGenome) return 0; // Disqualify constant expressions as we know we're not looking for them
-        return 1 / (squaredErrorSum / trainingCases.size());
-    }
-
-    private double effectiveError(double a, double b) {
-        return parameters.getErrorIsRelative() ? errorFraction(a, b) : a - b;
-    }
-
-    /** Calculate error in a way which is easy to understand (but which behaves badly when the target is around 0 */
-    public double calculateAverageError(RankingExpression genome) {
-        double errorSum=0;
-        for (Case trainingCase : trainingCases)
-            errorSum += saneAbs(trainingCase.targetValue() - genome.evaluate(trainingCase.arguments()).asDouble());
-        return errorSum/(double) trainingCases.size();
-    }
-
-    /** Calculate error in a way which is easy to understand (but which behaves badly when the target is around 0 */
-    public double calculateAverageErrorPercentage(RankingExpression genome) {
-        double errorFractionSum = 0;
-        for (Case trainingCase : trainingCases) {
-            double errorFraction = saneAbs(errorFraction(trainingCase.targetValue(), genome.evaluate(trainingCase.arguments()).asDouble()));
-            // System.out.println("Error %: " + (100 * errorFraction + " Target: " + trainingCase.targetValue() + " Learned: " + genome.evaluate(trainingCase.arguments()).asDouble()));
-            errorFractionSum += errorFraction;
-        }
-        return ( errorFractionSum/(double) trainingCases.size() ) *100;
-    }
-
-    private double errorFraction(double a, double b) {
-        double error = a - b;
-        if (error == 0 ) return 0; // otherwise a or b is different from 0
-        if (a != 0)
-            return error / a;
-        else
-            return error / b;
-    }
-
-    private double saneAbs(double d) {
-        if (Double.isInfinite(d) || Double.isNaN(d)) return Double.MAX_VALUE;
-        return Math.abs(d);
-    }
-
-    public static class Case {
-
-        private Context arguments;
-
-        private double targetValue;
-
-        public Case(Context arguments, double targetValue) {
-            this.arguments = arguments;
-            this.targetValue = targetValue;
-        }
-
-        public double targetValue() { return targetValue; }
-
-        public Context arguments() { return arguments; }
-
-    }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/caselist/CsvFileCaseList.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/caselist/CsvFileCaseList.java
deleted file mode 100644
index c7f4f848b71..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/caselist/CsvFileCaseList.java
+++ /dev/null
@@ -1,56 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga.caselist;
-
-import com.yahoo.searchlib.mlr.ga.TrainingSet;
-import com.yahoo.searchlib.rankingexpression.evaluation.Context;
-import com.yahoo.searchlib.rankingexpression.evaluation.MapContext;
-
-import java.util.Optional;
-
-/**
- * <p>A list of training set cases created by reading a file containing lines specifying a case
- * per line using the following syntax
- * <code>targetValue, argument1:value, argument2:value2, ...</code>
- * where arguments are identifiers and values are doubles.</p>
- *
- * <p>Comment lines starting with "#" are ignored.</p>
- *
- * @author bratseth
- */
-public class CsvFileCaseList extends FileCaseList {
-
-    public CsvFileCaseList(String fileName) {
-        super(fileName);
-    }
-
-    protected Optional<TrainingSet.Case> lineToCase(String line, int lineNumber) {
-        String[] elements = line.split(",");
-        if (elements.length<2)
-            throw new IllegalArgumentException("At line " + lineNumber + ": Expected a comma-separated case on the " +
-                    "form 'targetValue, argument1:value1, ...', but got '" + line );
-
-        double target;
-        try {
-            target = Double.parseDouble(elements[0].trim());
-        }
-        catch (NumberFormatException e) {
-            throw new IllegalArgumentException("At line " + lineNumber + ": Expected a target value double " +
-                    "at the start of the line, got '" + elements[0] + "'");
-        }
-
-        Context context = new MapContext();
-        for (int i=1; i<elements.length; i++) {
-            String[] argumentPair = elements[i].split(":");
-            try {
-                if (argumentPair.length != 2)  throw new IllegalArgumentException();
-                context.put(argumentPair[0].trim(),Double.parseDouble(argumentPair[1].trim()));
-            }
-            catch (IllegalArgumentException e) {
-                throw new IllegalArgumentException("At line " + lineNumber + ", element " + (i+1) +
-                        ": Expected argument on the form 'identifier:double', got '" + elements[i] + "'");
-            }
-        }
-        return Optional.of(new TrainingSet.Case(context, target));
-    }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/caselist/FileCaseList.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/caselist/FileCaseList.java
deleted file mode 100644
index 35a4d58d16c..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/caselist/FileCaseList.java
+++ /dev/null
@@ -1,73 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga.caselist;
-
-import com.yahoo.searchlib.mlr.ga.CaseList;
-import com.yahoo.searchlib.mlr.ga.TrainingParameters;
-import com.yahoo.searchlib.mlr.ga.TrainingSet;
-
-import java.io.BufferedReader;
-import java.io.FileReader;
-import java.io.IOException;
-import java.util.ArrayList;
-import java.util.Collections;
-import java.util.List;
-import java.util.Optional;
-
-/**
- * @author bratseth
- */
-public abstract class FileCaseList implements CaseList {
-
-    private List<TrainingSet.Case> cases = new ArrayList<>();
-
-    /**
-     * Reads a case list from file.
-     *
-     * @throws IllegalArgumentException if the file could not be found or opened
-     */
-    public FileCaseList(String fileName) {
-        try (BufferedReader reader = new BufferedReader(new FileReader(fileName))) {
-            String line;
-            int lineNumber=0;
-            while (null != (line=reader.readLine())) {
-                lineNumber++;
-                line = line.trim();
-                if (line.startsWith("#")) continue;
-                if (line.isEmpty()) continue;
-                Optional<TrainingSet.Case> newCase = lineToCase(line, lineNumber);
-                if (newCase.isPresent())
-                    cases.add(newCase.get());
-
-            }
-        }
-        catch (IOException | IllegalArgumentException e) {
-            throw new IllegalArgumentException("Could not create a case list from file '" + fileName + "'", e);
-        }
-    }
-
-    /** Returns the case constructed from reading a line, if any */
-    protected abstract Optional<TrainingSet.Case> lineToCase(String line, int lineNumber);
-
-    @Override
-    public List<TrainingSet.Case> cases() { return Collections.unmodifiableList(cases); }
-
-    /** Creates a file case list of the type specified in the parameters */
-    public static FileCaseList create(String fileName, TrainingParameters parameters) {
-        String format = parameters.getTrainingSetFormat();
-        if (format == null)
-            format = ending(fileName);
-
-        switch (format) {
-            case "csv" : return new CsvFileCaseList(fileName);
-            case "fv" : return new FvFileCaseList(fileName);
-            default : throw new IllegalArgumentException("Unknown file format '" + format + "'");
-        }
-    }
-
-    private static String ending(String fileName) {
-        int lastDot = fileName.lastIndexOf(".");
-        if (lastDot <= 0) return null;
-        return fileName.substring(lastDot + 1, fileName.length());
-    }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/caselist/FvFileCaseList.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/caselist/FvFileCaseList.java
deleted file mode 100644
index 0e5b2aac729..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/ga/caselist/FvFileCaseList.java
+++ /dev/null
@@ -1,59 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga.caselist;
-
-import com.yahoo.searchlib.mlr.ga.TrainingSet;
-import com.yahoo.searchlib.rankingexpression.evaluation.Context;
-import com.yahoo.searchlib.rankingexpression.evaluation.MapContext;
-
-import java.util.Optional;
-
-/**
- * A list of training set cases created by reading a file containing lines specifying a case
- * per line using the following syntax
- * <code>feature1\tfeature2\tfeature3\t...\ttarget1</code>
- * <p>
- * The first line contains the name of each feature in the same order.
- *
- * <p>Comment lines starting with "#" are ignored.</p>
- *
- * @author bratseth
- */
-// NOTE: If we get another type of case list it is time to abstract into a common CaseList base class
-public class FvFileCaseList extends FileCaseList {
-
-    private String[] argumentNames;
-
-    public FvFileCaseList(String fileName) {
-        super(fileName);
-    }
-
-    protected Optional<TrainingSet.Case> lineToCase(String line, int lineNumber) {
-        String[] values = line.split("\t");
-
-        if (argumentNames == null) { // first line
-            argumentNames = values;
-            return Optional.empty();
-        }
-
-        if (argumentNames.length != values.length)
-            throw new IllegalArgumentException("Wrong number of values at line " + lineNumber);
-
-
-        Context context = new MapContext();
-        for (int i = 0; i < values.length-1; i++)
-            context.put(argumentNames[i], toDouble(values[i], lineNumber));
-
-        double target = toDouble(values[values.length-1], lineNumber);
-        return Optional.of(new TrainingSet.Case(context, target));
-    }
-
-    private double toDouble(String s, int lineNumber) {
-        try {
-            return Double.parseDouble(s.trim());
-        } catch (NumberFormatException e) {
-            throw new IllegalArgumentException("At line " + lineNumber + ": Expected only double values, " +
-                                               "got '" + s + "'");
-        }
-    }
-
-}
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/mlr/gbdt/ExpressionAnalysis.java b/searchlib/src/main/java/com/yahoo/searchlib/mlr/gbdt/ExpressionAnalysis.java
deleted file mode 100644
index 16a4f6f931b..00000000000
--- a/searchlib/src/main/java/com/yahoo/searchlib/mlr/gbdt/ExpressionAnalysis.java
+++ /dev/null
@@ -1,425 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.gbdt;
-
-import com.yahoo.searchlib.rankingexpression.rule.SetMembershipNode;
-import com.yahoo.yolean.Exceptions;
-import com.yahoo.searchlib.mlr.ga.Individual;
-import com.yahoo.searchlib.mlr.ga.PrintingTracker;
-import com.yahoo.searchlib.mlr.ga.RankingExpressionCaseList;
-import com.yahoo.searchlib.mlr.ga.Trainer;
-import com.yahoo.searchlib.mlr.ga.TrainingParameters;
-import com.yahoo.searchlib.mlr.ga.TrainingSet;
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-import com.yahoo.searchlib.rankingexpression.evaluation.Context;
-import com.yahoo.searchlib.rankingexpression.evaluation.MapContext;
-import com.yahoo.searchlib.rankingexpression.evaluation.Value;
-import com.yahoo.searchlib.rankingexpression.parser.ParseException;
-import com.yahoo.searchlib.rankingexpression.rule.Arguments;
-import com.yahoo.searchlib.rankingexpression.rule.ArithmeticNode;
-import com.yahoo.searchlib.rankingexpression.rule.ComparisonNode;
-import com.yahoo.searchlib.rankingexpression.rule.CompositeNode;
-import com.yahoo.searchlib.rankingexpression.rule.ConstantNode;
-import com.yahoo.searchlib.rankingexpression.rule.ExpressionNode;
-import com.yahoo.searchlib.rankingexpression.rule.ReferenceNode;
-import com.yahoo.searchlib.rankingexpression.rule.IfNode;
-import com.yahoo.searchlib.rankingexpression.rule.NegativeNode;
-import com.yahoo.searchlib.rankingexpression.rule.TruthOperator;
-
-import java.io.BufferedReader;
-import java.io.FileNotFoundException;
-import java.io.FileReader;
-import java.io.IOException;
-import java.io.Reader;
-import java.util.ArrayList;
-import java.util.Collections;
-import java.util.HashMap;
-import java.util.HashSet;
-import java.util.List;
-import java.util.Map;
-import java.util.Random;
-
-/**
- * A standalone tool which analyzes a GBDT form ranking expression
- *
- * @author bratseth
- */
-public class ExpressionAnalysis {
-
-    private final Map<String, Feature> features = new HashMap<>();
-
-    private int currentTree;
-
-    private final RankingExpression expression;
-
-    public ExpressionAnalysis(RankingExpression expression) {
-        this.expression = expression;
-        if ( ! instanceOf(expression.getRoot(), ArithmeticNode.class)) return;
-        analyzeSum((ArithmeticNode)expression.getRoot());
-    }
-
-    /** Returns the expression analyzed by this */
-    public RankingExpression expression() { return expression; }
-
-    /** Returns the analysis of each feature in this expression as a read-only map indexed by feature name */
-    private Map<String, Feature> featureMap() {
-        return Collections.unmodifiableMap(features);
-    }
-
-    /** Returns list containing the analysis of each feature, sorted by decreasing usage */
-    private List<Feature> features() {
-        List<Feature> featureList = new ArrayList<>(features.values());
-        Collections.sort(featureList);
-        return featureList;
-    }
-
-    /** Returns the name of each feature, sorted by decreasing usage */
-    private List<String> featureNames() {
-        List<String> featureNameList = new ArrayList<>(features.values().size());
-        for (Feature feature : features())
-            featureNameList.add(feature.name());
-        return featureNameList;
-    }
-
-    private void analyzeSum(ArithmeticNode node) {
-        for (ExpressionNode child : node.children()) {
-            currentTree++;
-            analyze(child);
-        }
-    }
-
-    private void analyze(ExpressionNode node) {
-        if (node instanceof IfNode) {
-            analyzeIf((IfNode)node);
-        }
-
-        if (node instanceof CompositeNode) {
-            for (ExpressionNode child : ((CompositeNode)node).children())
-                analyze(child);
-        }
-    }
-
-    private void analyzeIf(IfNode node) {
-        if (node.getCondition() instanceof ComparisonNode)
-            analyzeComparisonIf(node);
-        else if (node.getCondition() instanceof SetMembershipNode)
-            analyzeSetMembershipIf(node);
-        else
-            System.err.println("Warning: Expected a comparison or set membership test, got " + node.getCondition().getClass());
-    }
-
-    private void analyzeComparisonIf(IfNode node) {
-        ComparisonNode comparison = (ComparisonNode)node.getCondition();
-
-        if (comparison.getOperator() != TruthOperator.SMALLER) {
-            System.err.println("Warning: This expression has " + comparison.getOperator() + " where we expect < :" +
-                               comparison);
-            return;
-        }
-
-        if ( ! instanceOf(comparison.getLeftCondition(), ReferenceNode.class)) return;
-        String featureName = ((ReferenceNode)comparison.getLeftCondition()).getName();
-
-        Double value = nodeValue(comparison.getRightCondition());
-        if (value == null) return;
-
-        ComparisonFeature feature = (ComparisonFeature)features.get(featureName);
-        if (feature == null) {
-            feature = new ComparisonFeature(featureName);
-            features.put(featureName, feature);
-        }
-        feature.isComparedTo(value, currentTree, average(node.getTrueExpression()), average(node.getFalseExpression()));
-    }
-
-    private void analyzeSetMembershipIf(IfNode node) {
-        SetMembershipNode membershipTest = (SetMembershipNode)node.getCondition();
-
-        if ( ! instanceOf(membershipTest.getTestValue(), ReferenceNode.class)) return;
-        String featureName = ((ReferenceNode)membershipTest.getTestValue()).getName();
-
-        SetMembershipFeature feature = (SetMembershipFeature)features.get(featureName);
-        if (feature == null) {
-            feature = new SetMembershipFeature(featureName);
-            features.put(featureName, feature);
-        }
-    }
-
-    /**
-     * Returns the value of a constant node, or a negative wrapping a constant.
-     * Warns and returns null if it is neither.
-     */
-    private Double nodeValue(ExpressionNode node) {
-        if (node instanceof NegativeNode) {
-            NegativeNode negativeNode = (NegativeNode)node;
-            if ( ! instanceOf(negativeNode.getValue(), ConstantNode.class)) return null;
-            return - ((ConstantNode)negativeNode.getValue()).getValue().asDouble();
-        }
-        else {
-            if ( ! instanceOf(node, ConstantNode.class)) return null;
-            return ((ConstantNode)node).getValue().asDouble();
-        }
-    }
-
-
-    /** Returns the average value of all the leaf constants below this */
-    private double average(ExpressionNode node) {
-        Sum sum = new Sum();
-        average(node, sum);
-        return sum.average();
-    }
-
-    private void average(ExpressionNode node, Sum sum) {
-        if (node instanceof CompositeNode) {
-            for (ExpressionNode child : ((CompositeNode)node).children())
-                average(child, sum);
-        }
-        else {
-            Double value = nodeValue(node);
-            if (value == null) return;
-            sum.add(value);
-        }
-    }
-
-    private boolean instanceOf(Object object, Class<?> clazz) {
-        if (clazz.isAssignableFrom(object.getClass())) return true;
-        System.err.println("Warning: This expression has " + object.getClass() + " where we expect " + clazz +
-                           ": Instance " + object);
-        return false;
-    }
-
-    private List<Context> generateArgumentSets(int count) {
-        List<Context> argumentSets = new ArrayList<>(count);
-        for (int i=0; i<count; i++) {
-            ArgumentIgnoringMapContext context = new ArgumentIgnoringMapContext();
-            for (Feature feature : features()) {
-                if (feature instanceof ComparisonFeature) {
-                    ComparisonFeature comparison = (ComparisonFeature)feature;
-                    context.put(comparison.name(),randomBetween(comparison.lowerBound(), comparison.upperBound()));
-                }
-                // TODO: else if (feature instanceof SetMembershipFeature)
-            }
-            argumentSets.add(context);
-        }
-        return argumentSets;
-    }
-
-    private Random random = new Random();
-    /** Returns a random value in [lowerBound, upperBound&gt; */
-    private double randomBetween(double lowerBound, double upperBound) {
-        return random.nextDouble()*(upperBound-lowerBound)+lowerBound;
-    }
-
-    private static class ArgumentIgnoringMapContext extends MapContext {
-
-        @Override
-        public Value get(String name, Arguments arguments,String output) {
-            return super.get(name, null, output);
-        }
-
-    }
-
-    /** Generates a textual report from analyzing this expression */
-    public String report() {
-        StringBuilder b = new StringBuilder();
-        b.append("Trees: " + currentTree).append("\n");
-        b.append("Features:\n");
-        for (Feature feature : features())
-            b.append("  " + feature).append("\n");
-        return b.toString();
-    }
-
-    private static final String usage = "\nUsage: ExpressionAnalysis [myExpressionFile.expression]";
-
-    public static void main(String[] args) {
-        if (args.length == 0) error("No arguments." + usage);
-
-        ExpressionAnalysis analysis = analysisFromFile(args[0]);
-
-        if (1==1) return; // Turn off ga training
-        if (args.length == 1) {
-            new GATraining(analysis);
-        }
-        else if (args.length == 2) {
-            try {
-                new LearntExpressionAnalysis(analysis, new RankingExpression(args[1]));
-            }
-            catch (ParseException e) {
-                error("Syntax error in argument expression: " + Exceptions.toMessageString(e));
-            }
-        }
-        else {
-            error("Unexpectedly got more than 2 arguments." + usage);
-        }
-
-    }
-
-    private static ExpressionAnalysis analysisFromFile(String fileName) {
-        try (Reader fileReader = new BufferedReader(new FileReader(fileName))) {
-            System.out.println("Analyzing " + fileName + "...");
-            ExpressionAnalysis analysis = new ExpressionAnalysis(new RankingExpression(fileReader));
-            System.out.println(analysis.report());
-            return analysis;
-        }
-        catch (FileNotFoundException e) {
-            error("Could not find '" + fileName + "'");
-        }
-        catch (IOException e) {
-            error("Failed reading '" + fileName + "': " + Exceptions.toMessageString(e));
-        }
-        catch (ParseException e) {
-            error("Syntax error in '" + fileName + "': " + Exceptions.toMessageString(e));
-        }
-        return null;
-    }
-
-    private static class LearntExpressionAnalysis {
-
-        public LearntExpressionAnalysis(ExpressionAnalysis analysis, RankingExpression learntExpression) {
-            int cases = 1000;
-            TrainingSet newTrainingSet = new TrainingSet(new RankingExpressionCaseList(analysis.generateArgumentSets(cases),
-                                                                                       analysis.expression()), new TrainingParameters());
-            Individual winner = new Individual(learntExpression, newTrainingSet);
-            System.out.println("With separate training set: " + winner.toShortString() + " (" + winner.calculateAverageError() + ")");
-        }
-
-    }
-
-    private static class GATraining {
-
-        public GATraining(ExpressionAnalysis analysis) {
-            int skipFeatures = 0;
-            int featureCount = analysis.featureNames().size();
-            int cases = 1000;
-            TrainingParameters parameters = new TrainingParameters();
-            parameters.setInitialSpeciesSize(50);
-            parameters.setSpeciesLifespan(50);
-            //parameters.setAllowConditions(false); // disallow non-smooth functions
-            parameters.setMaxExpressionDepth(8);
-            TrainingSet trainingSet = new TrainingSet(new RankingExpressionCaseList(analysis.generateArgumentSets(cases),
-                                                                                    analysis.expression()), parameters);
-            Trainer trainer = new Trainer(trainingSet, new HashSet<>(analysis.featureNames().subList(skipFeatures, featureCount)));
-
-            System.out.println("Learning ...");
-            RankingExpression learntExpression = trainer.train(parameters, new PrintingTracker(100, 0, 1));
-            System.out.println("Learnt expression: " + learntExpression);
-
-            // Check for overtraining
-            new LearntExpressionAnalysis(analysis, learntExpression);
-        }
-
-    }
-
-    private static void error(String message) {
-        System.err.println(message);
-        System.exit(1);
-    }
-
-    public abstract static class Feature implements Comparable<Feature> {
-
-        private final String name;
-
-        protected Feature(String name) {
-            this.name = name;
-        }
-
-        public String name() { return name; }
-
-        /** Primary sort by type, secondary by name */
-        @Override
-        public int compareTo(Feature other) {
-            int typeComparison = this.getClass().getName().compareTo(other.getClass().getName());
-            if (typeComparison != 0) return typeComparison;
-            return this.name.compareTo(other.name);
-        }
-
-    }
-
-    /** A feature used in comparisons. These are the ones on which our serious analysis is focused */
-    public static class ComparisonFeature extends Feature {
-
-        private double lowerBound = Double.MAX_VALUE;
-        private double upperBound = Double.MIN_VALUE;
-
-        /** The number of usages of this feature */
-        private int usages = 0;
-
-        /** The sum of the tree numbers where this is accessed */
-        private int treeNumberSum = 0;
-
-        /**
-         * The net times where the left values are smaller than the right values for this
-         * (which is a measure of correlation between input and output because the comparison is &lt;)
-         */
-        private int correlationCount = 0;
-
-        /**
-         * The sum difference in returned value between choosing the right and left branch due to this feature
-         */
-        private double netSum = 0;
-
-        public ComparisonFeature(String name) {
-            super(name);
-        }
-
-        public double lowerBound() { return lowerBound; }
-        public double upperBound() { return upperBound; }
-
-        public void isComparedTo(double value, int inTreeNumber, double leftAverage, double rightAverage) {
-            lowerBound = Math.min(lowerBound, value);
-            upperBound = Math.max(upperBound, value);
-            usages++;
-            treeNumberSum += inTreeNumber;
-            correlationCount += leftAverage < rightAverage ? 1 : -1;
-            netSum += rightAverage - leftAverage;
-        }
-
-        /** Override to do secondary sort by usages */
-        public int compareTo(Feature o) {
-            if ( ! (o instanceof ComparisonFeature)) return super.compareTo(o);
-            ComparisonFeature other = (ComparisonFeature)o;
-            return - Integer.compare(this.usages, other.usages);
-        }
-
-        @Override
-        public String toString() {
-            return "Numeric     feature: " + name() +
-                    ": range [" + lowerBound + ", " + upperBound + "]" +
-                    ", usages " + usages +
-                    ", average tree occurrence " + (treeNumberSum / usages) +
-                    ", correlation: " + (correlationCount / (double)usages) +
-                    ", net contribution: " + netSum;
-        }
-
-    }
-
-    /** A feature used in set membership tests */
-    public static class SetMembershipFeature extends Feature {
-
-        public SetMembershipFeature(String name) {
-            super(name);
-        }
-
-        @Override
-        public String toString() {
-            return "Categorical feature: " + name();
-        }
-
-    }
-
-    /** A sum which can returns its average */
-    private static class Sum {
-
-        private double sum;
-        private int count;
-
-        public void add(double value) {
-            sum+=value;
-            count++;
-        }
-
-        public double average() {
-            return sum / count;
-        }
-
-    }
-
-}
diff --git a/searchlib/src/main/sh/ga b/searchlib/src/main/sh/ga
deleted file mode 100644
index 009b9684160..00000000000
--- a/searchlib/src/main/sh/ga
+++ /dev/null
@@ -1,67 +0,0 @@
-#! /bin/sh
-# Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-
-# BEGIN environment bootstrap section
-# Do not edit between here and END as this section should stay identical in all scripts
-
-findpath () {
-    myname=${0}
-    mypath=${myname%/*}
-    myname=${myname##*/}
-    if [ "$mypath" ] && [ -d "$mypath" ]; then
-        return
-    fi
-    mypath=$(pwd)
-    if [ -f "${mypath}/${myname}" ]; then
-        return
-    fi
-    echo "FATAL: Could not figure out the path where $myname lives from $0"
-    exit 1
-}
-
-COMMON_ENV=libexec/vespa/common-env.sh
-
-source_common_env () {
-    if [ "$VESPA_HOME" ] && [ -d "$VESPA_HOME" ]; then
-        export VESPA_HOME
-        common_env=$VESPA_HOME/$COMMON_ENV
-        if [ -f "$common_env" ]; then
-            . $common_env
-            return
-        fi
-    fi
-    return 1
-}
-
-findroot () {
-    source_common_env && return
-    if [ "$VESPA_HOME" ]; then
-        echo "FATAL: bad VESPA_HOME value '$VESPA_HOME'"
-        exit 1
-    fi
-    if [ "$ROOT" ] && [ -d "$ROOT" ]; then
-        VESPA_HOME="$ROOT"
-        source_common_env && return
-    fi
-    findpath
-    while [ "$mypath" ]; do
-        VESPA_HOME=${mypath}
-        source_common_env && return
-        mypath=${mypath%/*}
-    done
-    echo "FATAL: missing VESPA_HOME environment variable"
-    echo "Could not locate $COMMON_ENV anywhere"
-    exit 1
-}
-
-findroot
-
-# END environment bootstrap section
-
-JAR=$VESPA_HOME/lib/jars/searchlib-deploy.jar
-if [[ "$1" == *.jar ]]; then
-    JAR=$1
-fi
-shift
-
-exec java -cp $JAR com.yahoo.searchlib.mlr.ga.Main "$@"
diff --git a/searchlib/src/main/sh/gbdt-analysis b/searchlib/src/main/sh/gbdt-analysis
deleted file mode 100755
index eae755689b0..00000000000
--- a/searchlib/src/main/sh/gbdt-analysis
+++ /dev/null
@@ -1,2 +0,0 @@
-# Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-java -cp target/searchlib.jar com.yahoo.searchlib.mlr.gbdt.ExpressionAnalysis $@
diff --git a/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/CsvFileCaseListTestCase.java b/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/CsvFileCaseListTestCase.java
deleted file mode 100644
index 68f705315ad..00000000000
--- a/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/CsvFileCaseListTestCase.java
+++ /dev/null
@@ -1,81 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga.test;
-
-import com.yahoo.searchlib.mlr.ga.TrainingParameters;
-import com.yahoo.searchlib.mlr.ga.caselist.CsvFileCaseList;
-import com.yahoo.yolean.Exceptions;
-import com.yahoo.searchlib.mlr.ga.TrainingSet;
-import org.junit.Test;
-import static org.junit.Assert.*;
-
-/**
- * @author bratseth
- */
-public class CsvFileCaseListTestCase {
-
-    private static final double delta = 0.000001;
-
-    @Test
-    public void testLegalFile() {
-        CsvFileCaseList list = new CsvFileCaseList("src/test/files/mlr/cases.csv");
-
-        assertEquals(3,list.cases().size());
-        {
-            TrainingSet.Case case1 = list.cases().get(0);
-            assertEquals(1.0, case1.targetValue(), delta);
-            assertEquals(2, case1.arguments().names().size());
-            assertEquals(2.0, case1.arguments().get("arg1").asDouble(),delta);
-            assertEquals(-1.3, case1.arguments().get("arg2").asDouble(),delta);
-        }
-
-        {
-            TrainingSet.Case case2 = list.cases().get(1);
-            assertEquals(-1.003, case2.targetValue(), delta);
-            assertEquals(1, case2.arguments().names().size());
-            assertEquals(500007, case2.arguments().get("arg1").asDouble(),delta);
-        }
-
-        {
-            TrainingSet.Case case3 = list.cases().get(2);
-            assertEquals(0, case3.targetValue(), delta);
-            assertEquals(1, case3.arguments().names().size());
-            assertEquals(1.0, case3.arguments().get("arg2").asDouble(),delta);
-        }
-
-        TrainingSet trainingSet = new TrainingSet(list, new TrainingParameters());
-        assertEquals(2, trainingSet.argumentNames().size());
-        assertTrue(trainingSet.argumentNames().contains("arg1"));
-        assertTrue(trainingSet.argumentNames().contains("arg2"));
-    }
-
-    @Test
-    public void testNonExistingFile() {
-        try {
-            new CsvFileCaseList("nosuchfile");
-        }
-        catch (IllegalArgumentException e) {
-            assertEquals("Could not create a case list from file 'nosuchfile': nosuchfile (No such file or directory)", Exceptions.toMessageString(e));
-        }
-    }
-
-    @Test
-    public void testInvalidFile1() {
-        try {
-            new CsvFileCaseList("src/test/files/mlr/cases-illegal1.csv");
-        }
-        catch (IllegalArgumentException e) {
-            assertEquals("Could not create a case list from file 'src/test/files/mlr/cases-illegal1.csv': At line 5, element 3: Expected argument on the form 'identifier:double', got ' arg2:'", Exceptions.toMessageString(e));
-        }
-    }
-
-    @Test
-    public void testInvalidFile2() {
-        try {
-            new CsvFileCaseList("src/test/files/mlr/cases-illegal2.csv");
-        }
-        catch (IllegalArgumentException e) {
-            assertEquals("Could not create a case list from file 'src/test/files/mlr/cases-illegal2.csv': At line 2: Expected a target value double at the start of the line, got '5db'", Exceptions.toMessageString(e));
-        }
-    }
-
-}
diff --git a/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/ExampleLearningSessions.java b/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/ExampleLearningSessions.java
deleted file mode 100644
index 4de83d16300..00000000000
--- a/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/ExampleLearningSessions.java
+++ /dev/null
@@ -1,110 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga.test;
-
-import com.yahoo.searchlib.mlr.ga.PrintingTracker;
-import com.yahoo.searchlib.mlr.ga.RankingExpressionCaseList;
-import com.yahoo.searchlib.mlr.ga.Trainer;
-import com.yahoo.searchlib.mlr.ga.TrainingParameters;
-import com.yahoo.searchlib.mlr.ga.TrainingSet;
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-import com.yahoo.searchlib.rankingexpression.evaluation.Context;
-import com.yahoo.searchlib.rankingexpression.evaluation.MapContext;
-import com.yahoo.searchlib.rankingexpression.parser.ParseException;
-
-import java.util.ArrayList;
-import java.util.List;
-
-/**
- * Main class - drives a learning session from the command line.
- *
- * @author  bratseth
- */
-public class ExampleLearningSessions {
-
-    public static void main(String[] args) throws ParseException {
-        test3();
-    }
-
-    // Always learnt precisely in less than a second
-    private static void test1() throws ParseException {
-        TrainingParameters parameters = new TrainingParameters();
-
-        RankingExpression target = new RankingExpression("2*x");
-        List<Context> arguments = new ArrayList<>();
-        arguments.add(MapContext.fromString("x:0").freeze());
-        arguments.add(MapContext.fromString("x:1").freeze());
-        arguments.add(MapContext.fromString("x:2").freeze());
-        TrainingSet trainingSet = new TrainingSet(new RankingExpressionCaseList(arguments, target), parameters);
-
-        Trainer trainer = new Trainer(trainingSet);
-
-        System.out.println("Learning ...");
-        RankingExpression learntExpression = trainer.train(parameters, new PrintingTracker());
-    }
-
-    // Solved well in a few seconds at most. Slow going thereafter.
-    private static void test2() throws ParseException {
-        TrainingParameters parameters = new TrainingParameters();
-        parameters.setSpeciesLifespan(100); // Shorter lifespan is faster?
-
-        RankingExpression target = new RankingExpression("5*x*x + 2*x + 13");
-        List<Context> arguments = new ArrayList<>();
-        arguments.add(MapContext.fromString("x:0").freeze());
-        arguments.add(MapContext.fromString("x:1").freeze());
-        arguments.add(MapContext.fromString("x:2").freeze());
-        arguments.add(MapContext.fromString("x:3").freeze());
-        arguments.add(MapContext.fromString("x:4").freeze());
-        arguments.add(MapContext.fromString("x:5").freeze());
-        arguments.add(MapContext.fromString("x:6").freeze());
-        arguments.add(MapContext.fromString("x:7").freeze());
-        arguments.add(MapContext.fromString("x:8").freeze());
-        arguments.add(MapContext.fromString("x:9").freeze());
-        arguments.add(MapContext.fromString("x:10").freeze());
-        arguments.add(MapContext.fromString("x:50").freeze());
-        arguments.add(MapContext.fromString("x:500").freeze());
-        arguments.add(MapContext.fromString("x:5000").freeze());
-        arguments.add(MapContext.fromString("x:50000").freeze());
-        TrainingSet trainingSet = new TrainingSet(new RankingExpressionCaseList(arguments, target), parameters);
-
-        Trainer trainer = new Trainer(trainingSet);
-
-        System.out.println("Learning ...");
-        RankingExpression learntExpression = trainer.train(parameters, new PrintingTracker());
-    }
-
-    // Solved well in at most a few minutes
-    private static void test3() throws ParseException {
-        TrainingParameters parameters = new TrainingParameters();
-        parameters.setAllowConditions(false); // disallow non-smooth functions: Speeds up learning of smooth ones greatly
-
-        RankingExpression target = new RankingExpression("-2.7*x*x*x + 5*x*x + 2*x + 13");
-        List<Context> arguments = new ArrayList<>();
-        arguments.add(MapContext.fromString("x:-50000").freeze());
-        arguments.add(MapContext.fromString("x:-5000").freeze());
-        arguments.add(MapContext.fromString("x:-500").freeze());
-        arguments.add(MapContext.fromString("x:-50").freeze());
-        arguments.add(MapContext.fromString("x:-10").freeze());
-        arguments.add(MapContext.fromString("x:0").freeze());
-        arguments.add(MapContext.fromString("x:1").freeze());
-        arguments.add(MapContext.fromString("x:2").freeze());
-        arguments.add(MapContext.fromString("x:3").freeze());
-        arguments.add(MapContext.fromString("x:4").freeze());
-        arguments.add(MapContext.fromString("x:5").freeze());
-        arguments.add(MapContext.fromString("x:6").freeze());
-        arguments.add(MapContext.fromString("x:7").freeze());
-        arguments.add(MapContext.fromString("x:8").freeze());
-        arguments.add(MapContext.fromString("x:9").freeze());
-        arguments.add(MapContext.fromString("x:10").freeze());
-        arguments.add(MapContext.fromString("x:50").freeze());
-        arguments.add(MapContext.fromString("x:500").freeze());
-        arguments.add(MapContext.fromString("x:5000").freeze());
-        arguments.add(MapContext.fromString("x:50000").freeze());
-        TrainingSet trainingSet = new TrainingSet(new RankingExpressionCaseList(arguments, target), parameters);
-
-        Trainer trainer = new Trainer(trainingSet);
-
-        System.out.println("Learning ...");
-        RankingExpression learntExpression = trainer.train(parameters, new PrintingTracker());
-    }
-
-}
diff --git a/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/MainTestCase.java b/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/MainTestCase.java
deleted file mode 100644
index f5febe2ab68..00000000000
--- a/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/MainTestCase.java
+++ /dev/null
@@ -1,57 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga.test;
-
-import com.yahoo.searchlib.mlr.ga.Evolvable;
-import com.yahoo.searchlib.mlr.ga.Main;
-import com.yahoo.searchlib.mlr.ga.PrintingTracker;
-import com.yahoo.searchlib.mlr.ga.Species;
-import com.yahoo.searchlib.mlr.ga.Tracker;
-import com.yahoo.searchlib.mlr.ga.TrainingParameters;
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-import org.junit.Test;
-import static org.junit.Assert.*;
-
-import java.util.List;
-
-/**
- * Tests the main class used from the command line
- *
- * @author bratseth
- */
-public class MainTestCase {
-
-    /** Tests that an extremely simple function expressed as cases in a file is learnt perfectly. */
-    @Test
-    public void testMain() {
-        SilentTestTracker tracker = new SilentTestTracker();
-        new Main(new String[] { "src/test/files/mlr/cases-linear.csv"}, tracker);
-        assertTrue(Double.isInfinite(tracker.winner.getFitness()));
-    }
-
-    private static class SilentTestTracker implements Tracker {
-
-        public Evolvable winner;
-
-        @Override
-        public void newSpecies(Species predecessor, int initialSize, List<RankingExpression> genePool) {
-        }
-
-        @Override
-        public void newSpeciesCreated(Species predecessor) {
-        }
-
-        @Override
-        public void speciesCompleted(Species predecessor) {
-        }
-
-        @Override
-        public void iteration(Species species, int generation) {
-        }
-
-        @Override
-        public void result(Evolvable winner) {
-            this.winner = winner;
-        }
-    }
-
-}
diff --git a/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/MockTrainingSetTestCase.java b/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/MockTrainingSetTestCase.java
deleted file mode 100644
index 2fc6e6cab3d..00000000000
--- a/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/MockTrainingSetTestCase.java
+++ /dev/null
@@ -1,46 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga.test;
-
-import com.yahoo.searchlib.mlr.ga.RankingExpressionCaseList;
-import com.yahoo.searchlib.mlr.ga.TrainingParameters;
-import com.yahoo.searchlib.mlr.ga.TrainingSet;
-import com.yahoo.searchlib.rankingexpression.RankingExpression;
-import com.yahoo.searchlib.rankingexpression.evaluation.Context;
-import com.yahoo.searchlib.rankingexpression.evaluation.MapContext;
-import com.yahoo.searchlib.rankingexpression.parser.ParseException;
-import org.junit.Test;
-import static org.junit.Assert.*;
-
-import java.util.ArrayList;
-import java.util.List;
-
-/**
- * @author bratseth
- */
-public class MockTrainingSetTestCase {
-
-    @Test
-    public void testMockTrainingSet() throws ParseException {
-        RankingExpression target = new RankingExpression("2*x");
-        List<Context> arguments = new ArrayList<>();
-        arguments.add(MapContext.fromString("x:0"));
-        arguments.add(MapContext.fromString("x:1"));
-        arguments.add(MapContext.fromString("x:2"));
-        TrainingSet trainingSet = new TrainingSet(new RankingExpressionCaseList(arguments, target), new TrainingParameters());
-        assertTrue(Double.isInfinite(trainingSet.evaluate(new RankingExpression("2*x"))));
-        assertEquals(4.0, trainingSet.evaluate(new RankingExpression("x")), 0.001);
-        assertEquals(0.0, trainingSet.evaluate(new RankingExpression("x/x")), 0.001);
-    }
-
-    @Test
-    public void testEvaluation() throws ParseException {
-        // with freezing
-        assertEquals(16.0,new RankingExpression("2*x*x*x").evaluate(MapContext.fromString("x:2").freeze()).asDouble(),0.0001);
-        assertEquals(8.0,new RankingExpression("x*x+x*x").evaluate(MapContext.fromString("x:2").freeze()).asDouble(),0.0001);
-
-        // without freezing
-        assertEquals(16.0,new RankingExpression("2*x*x*x").evaluate(MapContext.fromString("x:2")).asDouble(),0.0001);
-        assertEquals(8.0,new RankingExpression("x*x+x*x").evaluate(MapContext.fromString("x:2")).asDouble(),0.0001);
-    }
-
-}
diff --git a/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/TripAdvisorFileCaseList.java b/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/TripAdvisorFileCaseList.java
deleted file mode 100644
index 7945e2605b0..00000000000
--- a/searchlib/src/test/java/com/yahoo/searchlib/mlr/ga/test/TripAdvisorFileCaseList.java
+++ /dev/null
@@ -1,99 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.ga.test;
-
-import com.yahoo.searchlib.mlr.ga.CaseList;
-import com.yahoo.searchlib.mlr.ga.TrainingSet;
-import com.yahoo.searchlib.rankingexpression.evaluation.Context;
-import com.yahoo.searchlib.rankingexpression.evaluation.MapContext;
-
-import java.io.BufferedReader;
-import java.io.FileReader;
-import java.io.IOException;
-import java.util.*;
-
-/**
- * Reads a tripadvisor Kaggle challenge training set
- *
- * @author bratseth
- */
-public class TripAdvisorFileCaseList implements CaseList {
-
-    private List<TrainingSet.Case> cases = new ArrayList<>();
-    private Map<Integer,String> columnNames = new HashMap<>();
-
-    /**
-     * Reads a case list from file.
-     *
-     * @throws IllegalArgumentException if the file could not be found or opened
-     */
-    public TripAdvisorFileCaseList(String fileName) throws IllegalArgumentException {
-        System.out.print("Reading training data ");
-        try (BufferedReader reader = new BufferedReader(new FileReader(fileName))) {
-            String line;
-            readColumnNames(reader.readLine());
-            int lineNumber=1;
-            while (null != (line=reader.readLine())) {
-                lineNumber++;
-                line = line.trim();
-                if (line.startsWith("#")) continue;
-                if (line.isEmpty()) continue;
-                cases.add(lineToCase(line, lineNumber));
-            }
-        }
-        catch (IOException | IllegalArgumentException e) {
-            throw new IllegalArgumentException("Could not create a case list from file '" + fileName + "'", e);
-        }
-        System.out.println("done");
-    }
-
-    private void readColumnNames(String line) {
-        int columnNumber = 0;
-        for (String columnName : line.split(","))
-            columnNames.put(columnNumber++, columnName);
-    }
-
-    protected TrainingSet.Case lineToCase(String line, int lineNumber) {
-        if ((lineNumber % 10000) ==0)
-            System.out.print(".");
-
-        Map<String,Double> columnValues = readColumns(line);
-
-        double targetValue = columnValues.get("click_bool") + columnValues.get("booking_bool")*5;
-
-        Context context = new MapContext();
-        for (Map.Entry<String,Double> value : columnValues.entrySet()) {
-            if (value.getKey().equals("click_bool")) continue;
-            if (value.getKey().equals("gross_bookings_usd")) continue;
-            if (value.getKey().equals("booking_bool")) continue;
-            context.put(value.getKey(),value.getValue());
-        }
-        return new TrainingSet.Case(context, targetValue);
-    }
-
-    private Map<String, Double> readColumns(String line) {
-        Map<String,Double> columnValues = new LinkedHashMap<>();
-        int columnNumber = 0;
-        for (String valueString : line.split(",")) {
-            String columnName = columnNames.get(columnNumber++);
-            if (columnName.equals("date_time")) continue;
-            Double columnValue;
-            if (valueString.equals("NULL")) {
-                columnValue = 0.0;
-            }
-            else {
-                try {
-                    columnValue = Double.parseDouble(valueString);
-                }
-                catch (NumberFormatException e) {
-                    throw new IllegalArgumentException("Could not parse column '" + columnName + "'",e);
-                }
-            }
-            columnValues.put(columnName, columnValue);
-        }
-        return columnValues;
-    }
-
-    @Override
-    public List<TrainingSet.Case> cases() { return Collections.unmodifiableList(cases); }
-
-}
diff --git a/searchlib/src/test/java/com/yahoo/searchlib/mlr/gbdt/ExpressionAnalysisRunner.java b/searchlib/src/test/java/com/yahoo/searchlib/mlr/gbdt/ExpressionAnalysisRunner.java
deleted file mode 100644
index 28f90ebb0fc..00000000000
--- a/searchlib/src/test/java/com/yahoo/searchlib/mlr/gbdt/ExpressionAnalysisRunner.java
+++ /dev/null
@@ -1,19 +0,0 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.searchlib.mlr.gbdt;
-
-import org.junit.Ignore;
-import org.junit.Test;
-
-/**
- * Run an expression analyser without having to muck with classpath.
- *
- * @author bratseth
- */
-public class ExpressionAnalysisRunner {
-
-    @Test @Ignore
-    public void runAnalysis() {
-        ExpressionAnalysis.main(new String[] { "/Users/bratseth/Downloads/getty_mlr_001.expression"});
-    }
-
-}