Package aima.core.learning.neural

Examples of aima.core.learning.neural.Layer.feedForward()

33
34
35
36
37
38
39
40
41
42
43
    Vector expected = new Vector(2);
    expected.setValue(0, 0.321);
    expected.setValue(1, 0.368);

    Vector result1 = layer1.feedForward(inputVector1);
    Assert.assertEquals(expected.getValue(0), result1.getValue(0), 0.001);
    Assert.assertEquals(expected.getValue(1), result1.getValue(1), 0.001);

    Matrix weightMatrix2 = new Matrix(1, 2);
    weightMatrix2.set(0, 0, 0.09);
View Full Code Here
47
48
49
50
51
52
53
54
55
56
57
    biasVector2.setValue(0, 0.48);

    Layer layer2 = new Layer(weightMatrix2, biasVector2,
        new PureLinearActivationFunction());
    Vector inputVector2 = layer1.getLastActivationValues();
    Vector result2 = layer2.feedForward(inputVector2);
    Assert.assertEquals(0.446, result2.getValue(0), 0.001);
  }

  @Test
  public void testSensitivityMatrixCalculationFromErrorVector() {
View Full Code Here
67
68
69
70
71
72
73
74
75
76
77
        new LogSigActivationFunction());

    Vector inputVector1 = new Vector(1);
    inputVector1.setValue(0, 1);

    layer1.feedForward(inputVector1);

    Matrix weightMatrix2 = new Matrix(1, 2);
    weightMatrix2.set(0, 0, 0.09);
    weightMatrix2.set(0, 1, -0.17);
View Full Code Here
79
80
81
82
83
84
85
86
87
88
89
    biasVector2.setValue(0, 0.48);

    Layer layer2 = new Layer(weightMatrix2, biasVector2,
        new PureLinearActivationFunction());
    Vector inputVector2 = layer1.getLastActivationValues();
    layer2.feedForward(inputVector2);

    Vector errorVector = new Vector(1);
    errorVector.setValue(0, 1.261);
    LayerSensitivity layer2Sensitivity = new LayerSensitivity(layer2);
    layer2Sensitivity.sensitivityMatrixFromErrorMatrix(errorVector);
View Full Code Here
107
108
109
110
111
112
113
114
115
116
117
    LayerSensitivity layer1Sensitivity = new LayerSensitivity(layer1);

    Vector inputVector1 = new Vector(1);
    inputVector1.setValue(0, 1);

    layer1.feedForward(inputVector1);

    Matrix weightMatrix2 = new Matrix(1, 2);
    weightMatrix2.set(0, 0, 0.09);
    weightMatrix2.set(0, 1, -0.17);
View Full Code Here
119
120
121
122
123
124
125
126
127
128
129
    biasVector2.setValue(0, 0.48);

    Layer layer2 = new Layer(weightMatrix2, biasVector2,
        new PureLinearActivationFunction());
    Vector inputVector2 = layer1.getLastActivationValues();
    layer2.feedForward(inputVector2);

    Vector errorVector = new Vector(1);
    errorVector.setValue(0, 1.261);
    LayerSensitivity layer2Sensitivity = new LayerSensitivity(layer2);
    layer2Sensitivity.sensitivityMatrixFromErrorMatrix(errorVector);
View Full Code Here
153
154
155
156
157
158
159
160
161
162
163
    LayerSensitivity layer1Sensitivity = new LayerSensitivity(layer1);

    Vector inputVector1 = new Vector(1);
    inputVector1.setValue(0, 1);

    layer1.feedForward(inputVector1);

    Matrix weightMatrix2 = new Matrix(1, 2);
    weightMatrix2.set(0, 0, 0.09);
    weightMatrix2.set(0, 1, -0.17);
View Full Code Here
165
166
167
168
169
170
171
172
173
174
175
    biasVector2.setValue(0, 0.48);

    Layer layer2 = new Layer(weightMatrix2, biasVector2,
        new PureLinearActivationFunction());
    Vector inputVector2 = layer1.getLastActivationValues();
    layer2.feedForward(inputVector2);

    Vector errorVector = new Vector(1);
    errorVector.setValue(0, 1.261);
    LayerSensitivity layer2Sensitivity = new LayerSensitivity(layer2);
    layer2Sensitivity.sensitivityMatrixFromErrorMatrix(errorVector);
View Full Code Here
224
225
226
227
228
229
230
231
232
233
234
    LayerSensitivity layer1Sensitivity = new LayerSensitivity(layer1);

    Vector inputVector1 = new Vector(1);
    inputVector1.setValue(0, 1);

    layer1.feedForward(inputVector1);

    Matrix weightMatrix2 = new Matrix(1, 2);
    weightMatrix2.set(0, 0, 0.09);
    weightMatrix2.set(0, 1, -0.17);
View Full Code Here
237
238
239
240
241
242
243
244
245
246
247
    Layer layer2 = new Layer(weightMatrix2, biasVector2,
        new PureLinearActivationFunction());
    LayerSensitivity layer2Sensitivity = new LayerSensitivity(layer2);
    Vector inputVector2 = layer1.getLastActivationValues();
    layer2.feedForward(inputVector2);

    Vector errorVector = new Vector(1);
    errorVector.setValue(0, 1.261);
    layer2Sensitivity.sensitivityMatrixFromErrorMatrix(errorVector);
View Full Code Here
TOP
Copyright © 2018 www.massapi.com. 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.