Classifier1-Wrong Op

package com.xurmo.classifier;

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;



public class SimpleClassifier {

    public static 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() {
            // TODO Auto-generated method stub
            return this.x + " , " + this.y;
        }
    }

    @SuppressWarnings("resource")
    public static void main(String[] args) {

        Map<Point, Integer> points = new HashMap<SimpleClassifier.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, 2, new L1());
        learningAlgo.learningRate(1);

        // learningAlgo.alpha(1).stepOffset(1000);

        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();

        // now classify real data
        Vector v = new RandomAccessSparseVector(2);
        v.set(0, 0.5);
        v.set(1, 0.5);

        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(2);
        v.set(0, point.x);
        v.set(1, point.y);

        return v;
    }
}