problem with simple mahout classification example

[damodar shetyo]

Hi,

I am trying to build a simple model that can group points in 2D space.Am
training the model by giving few examples.After that i am using the model
to predict the group in which the any other points may fall.But am not
getting answer as expected.Am i missing something in my code or am i doing
something wrong?

public static void main(String[] args) {

           // points at (index%2)==0 belong to cluster 0 Eg (0,0) (0,1)
           // points at index%2 != 0 belong to cluster 1

            double [][] points =
{{0,0},{8,8},{0,1},{9,9},{1,0},{8,9},{1,1},{9,8}};


        OnlineLogisticRegression learningAlgo = new OnlineLogisticRegression();
        learningAlgo =  new OnlineLogisticRegression(2, 2, new L1());
        learningAlgo.alpha(1).stepOffset(1000);

        int i =0;
        System.out.println("training model  \n" );
        for(double point [] : points ){
            Vector v = new RandomAccessSparseVector(2);
            v.set(0, point[0]);
            v.set(1, point[1]);
            learningAlgo.train(i%2, v);
            i++;
        }

        learningAlgo.close();


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

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

        System.out.println("ans = " );
        System.out.println("Probability of cluster 0 = " + r.get(0));
        System.out.println("Probability of cluster 1 = " + r.get(1));

    }

op =

{0:0.45938608354117305,1:0.540613916458827}
ans =
Probability of cluster 0 = 0.45938608354117305
Probability of cluster 1 = 0.540613916458827

99 % of times the output show more probability for cluster 1.Why?

-- 
Regards,
Damodar Shetyo