MLP XOR classification problem with predict method [closed]

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Note : I misused the noun of my object as I named it Digits_Classifier putting in mind I want to classify digits but I started with this simple example to try to understand OpenCV but I faced this problem here :

Does anyone have any idea of why this code produces incorrect classification labels

public class Classifier {

// This is an MLP classifier
// We will use an MLP with structure 2-2-1 to do the task of classifying XOR problem

// MLP Attributes
ANN_MLP Digits_Classifier;
Mat Layers; // A mat contains number of neurons in each layer starting from the input till the output
Mat Training_Samples; // Training data
Mat Training_Responses; // Training data labels
Mat Test_Samples; // Test data 
Mat Test_Responses; // Test data labels that will be produced by MLP
int Row_Index , Col_Index; 
float Label;

// class constructor just declares / defines attributes
public Classifier()
{
    Digits_Classifier = ANN_MLP.create();

    Layers = new Mat(3,1,CvType.CV_32FC1);
    Training_Samples = new Mat(4,2,CvType.CV_32FC1);
    Training_Responses = new Mat(4,1,CvType.CV_32FC1);
    Test_Samples = new Mat(1,2,CvType.CV_32FC1);
    Test_Responses = new Mat(1,1,CvType.CV_32FC1);
}

public void Start()
{
    // Fill in Layers Mat
    int Layers_Arr[] = new int[]{2,2,1};
    for(int i=0 ; i<3 ; i++)
        Layers.put(i,0,Layers_Arr[i]);

    Row_Index = 0;
    Col_Index = 0;

    // Fill in Training_Samples Mat
    float[] Training_Samples_Arr = new float[]{0,0,0,1,1,0,1,1};
    for(int i=0 ; i<8 ; i++) {
        Training_Samples.put(Row_Index,Col_Index,Training_Samples_Arr[i]);
        Col_Index++;
        if(Col_Index >= 2)
        {
            Row_Index++;
            Col_Index = 0;
        }
    }

    // Fill in Training_Responses Mat
    float[] Training_Responses_Arr = new float[]{0,1,1,0};
    for(int i=0 ; i<4 ; i++)
        Training_Responses.put(i,0,Training_Responses_Arr[i]);

    // Fill in Test_Samples Mat
    double[] Test_Samples_Arr = new double[] {1.0,0.0};
    for(int i=0 ; i<2 ; i++)
        Test_Samples.put(0,i,Test_Samples_Arr[i]);

    Digits_Classifier.setLayerSizes(Layers);

    // The other 2 parameters other than type are Alpha and Beta
    Digits_Classifier.setActivationFunction(ANN_MLP.SIGMOID_SYM, 1.0, 1.0);

    // Term_Criteria object is created with 3 parameters : type , Iterations_Num , Error_Limit
    TermCriteria Digits_Classifier_Term_Criteria = new TermCriteria(TermCriteria.EPS,500,0.001);
    Digits_Classifier.setTermCriteria(Digits_Classifier_Term_Criteria);

    // the other 2 parameters other than type are momentum and weight scales
    Digits_Classifier.setTrainMethod(ANN_MLP.BACKPROP,0.1,0.1);

    Digits_Classifier.train(Training_Samples,Ml.ROW_SAMPLE,Training_Responses);

    // I think this method is the source of problem I face. 
    Label = Digits_Classifier.predict(Test_Samples,Test_Responses,StatModel.RAW_OUTPUT);
}

}

• So to summarize this is a 2-2-1 Neural net I use to perform XOR problem. I trained the network by using train method just once I then tried to predict what will the output be for test_sample such as (1 , 0) but the predict method returns 0 although it must be one and another thing is that I provided this example as a training sample what is the problem ?

• Another thing I want to ask about is that I defined Layers to be 3x1 Mat i.e. to have 3 layers one of them is the hidden one but when I use function getweights(int Layer_Index) it accepts until Layer_Index = 4 i.e. I have 5 layers so what ?

Note : I have ... (more)