Package org.encog.util.normalize.input

Examples of org.encog.util.normalize.input.InputField

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      {6.0,7.0,8.0,9.0} };
  private static final Logger log = LoggerFactory
  .getLogger(TemporalPredictionHelper.class);
  public static void main(String[] argv){
//    TemporalPoint point = new TemporalPoint( [number of values] );
    InputField ifield = new BasicInputField();
    ifield.setCurrentValue(100);
    ifield.setMin(0);
    ifield.setMax(200);
    OutputFieldRangeMapped orm = new OutputFieldRangeMapped(ifield,-1,1);
    log.info(String.valueOf(orm.calculate(0)));
    log.info(String.valueOf(orm.convertBack(0)));
   

    InputField a,b;
    double[][] arrayOutput = new double[2][2];
        
    BasicNeuralDataSet dataset = new
    BasicNeuralDataSet(ARRAY_2D,null);
        
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  public static final double[] ARRAY_1D = { 1.0,2.0,3.0,4.0,5.0 };
  public static final double[][] ARRAY_2D = { {1.0,2.0,3.0,4.0,5.0},
  {6.0,7.0,8.0,9.0} };
 
  private DataNormalization create1D(double[] arrayOutput) {
    InputField a;
       
    NormalizationStorageArray1D target = new NormalizationStorageArray1D(arrayOutput);
   
    DataNormalization norm = new DataNormalization();
    norm.setReport(new NullStatusReportable());
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    norm.addOutputField(new OutputFieldRangeMapped(a,0.1,0.9));
    return norm;
  }
 
  private DataNormalization create2D(double[][] arrayOutput) {
    InputField a,b;
       
    NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
   
    DataNormalization norm = new DataNormalization();
    norm.setReport(new NullStatusReportable());
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public class TestMultiplicative extends TestCase {
  double[][] SAMPLE1 = {{-10,5,15},{-2,1,3}};
 
  public DataNormalization create(double[][] arrayOutput) {
    InputField a;
    InputField b;
    InputField c;
       
    NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
    MultiplicativeGroup group = new MultiplicativeGroup();
    DataNormalization norm = new DataNormalization();
    norm.setReport(new NullStatusReportable());
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  public static final double[][] ARRAY_2D = { {1.0,2.0,3.0,4.0,5.0},
  {6.0,7.0,8.0,9.0} };
 
  private DataNormalization create(double[][] arrayOutput) {
    InputField a,b;
   
   
    NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
    OutputFieldEncode a1;
    OutputFieldEncode b1;
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    {1.0,2.0,3.0,4.0,5.0},
    {1.0,2.0,3.0,4.0,5.0},
    {2.0,2.0,3.0,4.0,5.0} };
 
    private DataNormalization createIntegerBalance() {
      InputField a,b;
      double[][] arrayOutput = new double[3][2];
     
     
     
      NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
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      check(norm,3);
    }
   
    private DataNormalization createRangeSegregate()
    {
      InputField a,b;
      double[][] arrayOutput = new double[1][2];
     
      RangeSegregator s;
     
      NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
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      check(norm,1);
    }
   
    private DataNormalization createSampleSegregate()
    {
      InputField a,b;
      double[][] arrayOutput = new double[6][2];
     
      NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
     
      DataNormalization norm = new DataNormalization();
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      check(norm,6);
    }
   
    public DataNormalization createIndexSegregate()
    {
      InputField a,b;
      double[][] arrayOutput = new double[6][2];
     
      NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
     
      DataNormalization norm = new DataNormalization();
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  public static final double[][] ARRAY_2D = { {1.0,2.0,3.0,4.0,5.0},
    {6.0,7.0,8.0,9.0} };
 
 
  private DataNormalization create() {
    InputField a,b;
    double[][] arrayOutput = new double[2][2];
   
    BasicNeuralDataSet dataset = new BasicNeuralDataSet(ARRAY_2D,null);
   
    NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
View Full Code Here
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Related Classes of org.encog.util.normalize.input.InputField

  • com.narirelays.ems.neuralnetwork.TemporalPredictionHelper
  • org.encog.util.normalize.TestMapped
  • org.encog.util.normalize.TestMultiplicative
  • org.encog.util.normalize.TestNormArray
  • org.encog.util.normalize.TestNormCSV
  • org.encog.util.normalize.TestNormDataSet
  • org.encog.util.normalize.TestSegregate
  • org.encog.util.normalize.TestZAxis
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