com.sixgroup.samplerecommender.Point.java Source code

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Here is the source code for com.sixgroup.samplerecommender.Point.java

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package com.sixgroup.samplerecommender;

import java.util.HashMap;
import java.util.Map;

import org.apache.mahout.classifier.sgd.L1;
import org.apache.mahout.classifier.sgd.OnlineLogisticRegression;
import org.apache.mahout.math.DenseVector;
import org.apache.mahout.math.RandomAccessSparseVector;
import org.apache.mahout.math.Vector;

class Point {
    public int x;
    public int y;

    public Point(int x, int y) {
        this.x = x;
        this.y = y;
    }

    @Override
    public boolean equals(Object arg0) {
        Point p = (Point) arg0;
        return ((this.x == p.x) && (this.y == p.y));
    }

    @Override
    public String toString() {
        return this.x + " , " + this.y;
    }
}

public class SampleRecommender {

    public static void main(String[] args) {

        Map<Point, Integer> points = new HashMap<Point, Integer>();

        points.put(new Point(0, 0), 0);
        points.put(new Point(1, 1), 0);
        points.put(new Point(1, 0), 0);
        points.put(new Point(0, 1), 0);
        points.put(new Point(2, 2), 0);

        points.put(new Point(8, 8), 1);
        points.put(new Point(8, 9), 1);
        points.put(new Point(9, 8), 1);
        points.put(new Point(9, 9), 1);

        OnlineLogisticRegression learningAlgo = new OnlineLogisticRegression();
        learningAlgo = new OnlineLogisticRegression(2, 3, new L1());
        learningAlgo.lambda(0.1);
        learningAlgo.learningRate(10);

        System.out.println("training model  \n");

        for (Point point : points.keySet()) {

            Vector v = getVector(point);
            System.out.println(point + " belongs to " + points.get(point));
            learningAlgo.train(points.get(point), v);
        }

        learningAlgo.close();

        Vector v = new RandomAccessSparseVector(3);
        v.set(0, 0.5);
        v.set(1, 0.5);
        v.set(2, 1);

        Vector r = learningAlgo.classifyFull(v);
        System.out.println(r);

        System.out.println("ans = ");
        System.out.println("no of categories = " + learningAlgo.numCategories());
        System.out.println("no of features = " + learningAlgo.numFeatures());
        System.out.println("Probability of cluster 0 = " + r.get(0));
        System.out.println("Probability of cluster 1 = " + r.get(1));

    }

    public static Vector getVector(Point point) {
        Vector v = new DenseVector(3);
        v.set(0, point.x);
        v.set(1, point.y);
        v.set(2, 1);
        return v;
    }
}