public PassiveAggressive copy() { close(); PassiveAggressive r = new PassiveAggressive(numCategories(), numFeatures()); r.copyFrom(this); return r; }
@Override public void train(int actual, Vector instance) { train(0, null, actual, instance); }
@Override public Vector classify(Vector instance) { Vector result = classifyNoLink(instance); // Convert to probabilities by exponentiation. double max = result.maxValue(); result.assign(Functions.minus(max)).assign(Functions.EXP); result = result.divide(result.norm(1)); return result.viewPart(1, result.size() - 1); }
@Test public void testPassiveAggressive() throws IOException { Vector target = readStandardData(); PassiveAggressive pa = new PassiveAggressive(2,8).learningRate(0.1); train(getInput(), target, pa); test(getInput(), target, pa, 0.11, 0.31); }
@Override public Vector classify(Vector instance) { Vector result = classifyNoLink(instance); // Convert to probabilities by exponentiation. double max = result.maxValue(); result.assign(Functions.minus(max)).assign(Functions.EXP); result = result.divide(result.norm(1)); return result.viewPart(1, result.size() - 1); }
public PassiveAggressive copy() { close(); PassiveAggressive r = new PassiveAggressive(numCategories(), numFeatures()); r.copyFrom(this); return r; }
@Override public Vector classify(Vector instance) { Vector result = classifyNoLink(instance); // Convert to probabilities by exponentiation. double max = result.maxValue(); result.assign(Functions.minus(max)).assign(Functions.EXP); result = result.divide(result.norm(1)); return result.viewPart(1, result.size() - 1); }
@Override public void train(int actual, Vector instance) { train(0, null, actual, instance); }
public PassiveAggressive copy() { close(); PassiveAggressive r = new PassiveAggressive(numCategories(), numFeatures()); r.copyFrom(this); return r; }
lossSum = 0; Vector result = classifyNoLink(instance); double myScore = result.get(actual);
@Override public void train(long trackingKey, int actual, Vector instance) { train(trackingKey, null, actual, instance); }
lossSum = 0; Vector result = classifyNoLink(instance); double myScore = result.get(actual);
@Override public void train(long trackingKey, int actual, Vector instance) { train(trackingKey, null, actual, instance); }
lossSum = 0; Vector result = classifyNoLink(instance); double myScore = result.get(actual);
@Override public void train(long trackingKey, int actual, Vector instance) { train(trackingKey, null, actual, instance); }
@Override public void train(int actual, Vector instance) { train(0, null, actual, instance); }