Package org.encog.neural.networks.training.propagation

Examples of org.encog.neural.networks.training.propagation.TrainingContinuation

53
54
55
56
57
58
59
60
61
62
63
    rprop1.iteration();
   
    rprop2.iteration();
    rprop2.iteration();
   
    TrainingContinuation cont = rprop2.pause();
   
    ResilientPropagation rprop3 = new ResilientPropagation(net2,trainingSet);
    rprop3.resume(cont);
   
    rprop1.iteration();
View Full Code Here
81
82
83
84
85
86
87
88
89
90
91
92
93
94
    rprop1.iteration();
   
    rprop2.iteration();
    rprop2.iteration();
   
    TrainingContinuation cont = rprop2.pause();
   
    EncogDirectoryPersistence.saveObject(EG_FILENAME, cont);
    TrainingContinuation cont2 = (TrainingContinuation)EncogDirectoryPersistence.loadObject(EG_FILENAME);
   
    ResilientPropagation rprop3 = new ResilientPropagation(net2,trainingSet);
    rprop3.resume(cont2);
   
    rprop1.iteration();
View Full Code Here
182
183
184
185
186
187
188
189
190
191
   *
   * @return A training continuation object to continue with.
   */
  @Override
  public TrainingContinuation pause() {
    final TrainingContinuation result = new TrainingContinuation();
    result.setTrainingType(this.getClass().getSimpleName());
    result.set(Backpropagation.LAST_DELTA, this.lastDelta);
    return result;
  }
View Full Code Here
52
53
54
55
56
57
58
59
60
61
62
   
    // train network 2, continue
    ResilientPropagation rprop2 = new ResilientPropagation(network2,trainingData);
    rprop2.iteration();
    rprop2.iteration();
    TrainingContinuation state = rprop2.pause();
    rprop2 = new ResilientPropagation(network2,trainingData);
    rprop2.resume(state);
    rprop2.iteration();
    rprop2.iteration();
   
View Full Code Here
85
86
87
88
89
90
91
92
93
94
95
   
    // train network 2, continue
    Backpropagation rprop2 = new Backpropagation(network2,trainingData,0.4,0.4);
    rprop2.iteration();
    rprop2.iteration();
    TrainingContinuation state = rprop2.pause();
    rprop2 = new Backpropagation(network2,trainingData,0.4,0.4);
    rprop2.resume(state);
    rprop2.iteration();
    rprop2.iteration();
   
View Full Code Here
202
203
204
205
206
207
208
209
210
211
212
213
214
215
   *
   * @return A training continuation object to continue with.
   */
  @Override
  public TrainingContinuation pause() {
    final TrainingContinuation result = new TrainingContinuation();

    result.setTrainingType(this.getClass().getSimpleName());

    result.set(ResilientPropagation.LAST_GRADIENTS,getLastGradient());
    result.set(ResilientPropagation.UPDATE_VALUES,getUpdateValues());

    return result;
  }
View Full Code Here
171
172
173
174
175
176
177
178
179
180
   *
   * @return A training continuation object to continue with.
   */
  @Override
  public TrainingContinuation pause() {
    final TrainingContinuation result = new TrainingContinuation();
    result.setTrainingType(this.getClass().getSimpleName());
    result.set(QuickPropagation.LAST_GRADIENTS, this.getLastGradient());
    return result;
  }
View Full Code Here
TOP

Related Classes of org.encog.neural.networks.training.propagation.TrainingContinuation

  • org.encog.examples.neural.resume.TrainResume
  • org.encog.neural.networks.training.propagation.back.Backpropagation
  • org.encog.neural.networks.training.propagation.quick.QuickPropagation
  • org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
  • org.encog.neural.networks.training.TestTrainingContinuation
  • org.encog.persist.TestPersistTrainingContinuation
  • org.encog.workbench.tabs.training.BasicTrainingProgress
    • 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.