LMS 機器學習方法

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public abstract class LMS {
    Object[] examples;
    double[] values;
    int[] successors;
    double[] weights;

    public LMS(Object[] E, double[] V, int[] S, double[] W) {
        examples = E; values = V; successors = S; weights = W;
    }

    public void learn() {
        // For each training example (e, V(s)) where  s = successor(e)
        for (int ei=0; ei<examples.length; ei++) {
            Object e  = examples[ei];
            // use the current weight to calculate V(e)
            double ve = value(e);
            double vs = values[successors[ei]];
            // For each weight wi, update it as
                // wi = wi + c( V(s) - V(e) )
            for (int wi=0; wi<weights.length; wi++)
                weights[wi] = weights[wi]+0.001 * (vs - ve);
        }
        System.out.print("w=");
        for (int wi=0; wi<weights.length; wi++)
            System.out.print(weights[wi]+",");
        System.out.println();
    }

    public abstract double value(Object e);
}

public class LMSTest extends LMS {    
    public static void main(String[] args) {
        Object[]     E = {new Double(1), new Double(3), new Double(5)};
        double[]       V = {2, 4, 6};
        int[]         S = {0, 1, 2};
        double[]    W = {0,0};

        LMSTest learner = new LMSTest(E,V,S,W);
        for (int i=0; i<1000; i++)
            learner.learn();
    }

    public LMSTest(Object[] E, double[] V, int[] S, double[] W) {
        super(E,V,S,W);
    }

    public double value(Object example) {
        double x = ((Double) example).doubleValue();
        return weights[0]+weights[1]*x;
    }
}

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page revision: 11, last edited: 11 Sep 2010 00:11

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