com.expleague.ml.cli.builders.methods.impl.RidgeRegressionLeavesObliviousTreeBuilder Maven / Gradle / Ivy
package com.expleague.ml.cli.builders.methods.impl;
import com.expleague.commons.func.Factory;
import com.expleague.commons.random.FastRandom;
import com.expleague.ml.BFGrid;
import com.expleague.ml.methods.MultipleVecOptimization;
import com.expleague.ml.methods.VecOptimization;
import com.expleague.ml.methods.trees.GreedyObliviousTree;
import com.expleague.ml.methods.trees.GreedyObliviousTreeWithVecOptimizationLeaves;
import com.expleague.ml.loss.L2;
import com.expleague.ml.loss.WeightedLoss;
import com.expleague.ml.methods.linearRegressionExperiments.MultipleRidgeRegression;
/**
* User: noxoomo
*/
public class RidgeRegressionLeavesObliviousTreeBuilder implements Factory {
public static FastRandom defaultRandom;
public static Factory defaultGridBuilder;
private Factory gridBuilder = defaultGridBuilder;
public FastRandom random = defaultRandom;
private int depth = 6;
private double lambda = 1.0;
public void setLambda(final double lambda) {
this.lambda = lambda;
}
public void setDepth(final int depth) {
this.depth = depth;
}
public void setGridBuilder(final Factory gridBuilder) {
this.gridBuilder = gridBuilder;
}
public void setRandom(final FastRandom random) {
this.random = random;
}
@Override
public VecOptimization create() {
final GreedyObliviousTree tree = new GreedyObliviousTree<>(gridBuilder.create(),depth);
final MultipleVecOptimization leafLearner = new MultipleRidgeRegression(lambda);
return new GreedyObliviousTreeWithVecOptimizationLeaves(tree,leafLearner,random);
}
}
© 2015 - 2024 Weber Informatics LLC | Privacy Policy