Package org.encog.util.normalize.target

Examples of org.encog.util.normalize.target.NormalizationStorageArray2D

35
36
37
38
39
40
41
42
43
44
45
    double[][] arrayOutput = new double[2][2];
        
    BasicNeuralDataSet dataset = new
    BasicNeuralDataSet(ARRAY_2D,null);
        
    NormalizationStorageArray2D target = new
    NormalizationStorageArray2D(arrayOutput);
        
    DataNormalization norm = new DataNormalization();
    norm.setReport(new NullStatusReportable());
    norm.setTarget(target);
View Full Code Here
55
56
57
58
59
60
61
62
63
64
65
  }
 
  private DataNormalization create2D(double[][] arrayOutput) {
    InputField a,b;
       
    NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
   
    DataNormalization norm = new DataNormalization();
    norm.setReport(new NullStatusReportable());
    norm.setTarget(target);
    norm.addInputField(a = new InputFieldArray2D(false,ARRAY_2D,0));
View Full Code Here
40
41
42
43
44
45
46
47
48
49
50
  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());
    norm.setTarget(target);
    norm.addInputField(a = new InputFieldArray2D(false,SAMPLE1,0));
View Full Code Here
40
41
42
43
44
45
46
47
48
49
50
 
  private DataNormalization create(double[][] arrayOutput) {
    InputField a,b;
   
   
    NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
    OutputFieldEncode a1;
    OutputFieldEncode b1;
   
    DataNormalization norm = new DataNormalization();
    norm.setReport(new NullStatusReportable());
View Full Code Here
49
50
51
52
53
54
55
56
57
58
59
      InputField a,b;
      double[][] arrayOutput = new double[3][2];
     
     
     
      NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
     
      DataNormalization norm = new DataNormalization();
      norm.setReport(new NullStatusReportable());
      norm.setTarget(target);
      norm.addInputField(a = new InputFieldArray2D(false,ARRAY_2D,0));
View Full Code Here
82
83
84
85
86
87
88
89
90
91
92
      InputField a,b;
      double[][] arrayOutput = new double[1][2];
     
      RangeSegregator s;
     
      NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
     
      DataNormalization norm = new DataNormalization();
      norm.setReport(new NullStatusReportable());
      norm.setTarget(target);
      norm.addInputField(a = new InputFieldArray2D(false,ARRAY_2D,0));
View Full Code Here
108
109
110
111
112
113
114
115
116
117
118
    private DataNormalization createSampleSegregate()
    {
      InputField a,b;
      double[][] arrayOutput = new double[6][2];
     
      NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
     
      DataNormalization norm = new DataNormalization();
      norm.setReport(new NullStatusReportable());
      norm.setTarget(target);
      norm.addInputField(a = new InputFieldArray2D(false,ARRAY_2D,0));
View Full Code Here
133
134
135
136
137
138
139
140
141
142
143
    public DataNormalization createIndexSegregate()
    {
      InputField a,b;
      double[][] arrayOutput = new double[6][2];
     
      NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
     
      DataNormalization norm = new DataNormalization();
      norm.setReport(new NullStatusReportable());
      norm.setTarget(target);
      norm.addInputField(a = new InputFieldArray2D(false,ARRAY_2D,0));
View Full Code Here
44
45
46
47
48
49
50
51
52
53
54
    InputField a,b;
    double[][] arrayOutput = new double[2][2];
   
    BasicNeuralDataSet dataset = new BasicNeuralDataSet(ARRAY_2D,null);
   
    NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
   
    DataNormalization norm = new DataNormalization();
    norm.setReport(new NullStatusReportable());
    norm.setTarget(target);
    norm.addInputField(a = new InputFieldMLDataSet(false,dataset,0));
View Full Code Here
90
91
92
93
94
95
96
97
    norm.addOutputField(new OutputFieldRangeMapped(a,0.1,0.9));
    norm.addOutputField(new OutputFieldRangeMapped(b,0.1,0.9));
    norm.addOutputField(new OutputFieldRangeMapped(c,0.1,0.9));
    norm.addOutputField(new OutputFieldRangeMapped(d,0.1,0.9));
    norm.addOutputField(new OutputFieldRangeMapped(e,0.1,0.9));
    norm.setTarget(new NormalizationStorageArray2D(outputArray));
    return norm;
  }
View Full Code Here
TOP

Related Classes of org.encog.util.normalize.target.NormalizationStorageArray2D

  • 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
    • Copyright © 2018 www.massapicom. All rights reserved.
    All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.