src/core/preprocess/Normalizer.java
public void minMaxSample(MMatrix data) throws NeuralNetworkException {
        HashMap<Integer, MMatrix> inputData = new HashMap<>();
        inputData.put(0, data);
        minMaxSamples (inputData, 0, 1, false, null);
    }
/**
     * Executes min max normalization.<br>
     *
     * @param data data to be normalized.
     * @throws NeuralNetworkException throws exception if normalizer is not yet adjusted.
     */
Executes min max normalization.
@param data data to be normalized.
@throws NeuralNetworkException throws exception if normalizer is not yet adjusted.
Executes min max normalization . @param data data to be normalized . @throws NeuralNetworkException throws exception if normalizer is not yet adjusted .
public void minMaxSample(MMatrix data) throws NeuralNetworkException {
        HashMap<Integer, MMatrix> inputData = new HashMap<>();
        inputData.put(0, data);
        minMaxSamples (inputData, 0, 1, false, null);
    }
public void minMaxSample ( MMatrix data ) throws NeuralNetworkException { HashMap < Integer , MMatrix > inputData = new HashMap < > ( ) ; inputData . put ( 0 , data ) ; minMaxSamples ( inputData , 0 , 1 , false , null ) ; }
Executes min max normalization.<br>
 @param data data to be normalized.
Executes min max normalization . <br > @param data data to be normalized .