package com.etsy.conjecture.model;
import com.etsy.conjecture.Utilities;
import com.etsy.conjecture.data.BinaryLabel;
import com.etsy.conjecture.data.LabeledInstance;
import com.etsy.conjecture.data.StringKeyedVector;
public class MIRA extends UpdateableLinearModel<BinaryLabel> {
private static final long serialVersionUID = 1L;
public MIRA() {
super(new MIRAOptimizer());
}
public MIRA(StringKeyedVector param, SGDOptimizer optimizer) {
super(param, optimizer);
}
@Override
public double loss(LabeledInstance<BinaryLabel> instance) {
double label = instance.getLabel().getAsPlusMinus();
double prediction = param.dot(instance.getVector());
double loss = Math.max(0, 1d - label * prediction);
return loss;
}
@Override
public BinaryLabel predict(StringKeyedVector instance) {
double inner = param.dot(instance);
return new BinaryLabel(Utilities.logistic(inner));
}
@Override
public StringKeyedVector getGradients(LabeledInstance<BinaryLabel> instance) {
StringKeyedVector gradients = instance.getVector().copy();
double label = instance.getLabel().getAsPlusMinus();
double prediction = param.dot(instance.getVector());
double loss = Math.max(0, 1d - label * prediction);
if (loss > 0) {
double norm = instance.getVector().LPNorm(2d);
double tau = loss / (norm * norm);
gradients.mul(tau * label);
return gradients;
} else {
return new StringKeyedVector();
}
}
@Override
protected String getModelType() {
return "MIRA";
}
}