Package org.encog.workbench.dialogs.common

Examples of org.encog.workbench.dialogs.common.DoubleField

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   */
  public InputManhattan() {
    super(true);
    setTitle("Train Manhattan Update Rule");
   
    addProperty(this.fixedDelta = new DoubleField("fixed delta","Fixed Delta",true,0,-1));
    render();
    this.fixedDelta.setValue(0.000001);

  }
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    list.add("2D RBF - MexicanHat");
    list.add("2D RBF - Multiquadric");
    list.add("2D RBF - InverseMultiquadric");
   
    setTitle("Train SOM Network");
    addProperty(this.learningRate = new DoubleField("learning rate","Learning Rate",true,0,-1));
    addProperty(this.neighborhoodType = new ComboBoxField("neighborhood","Neighborhood Type",true,list));
    addProperty(this.rbfWidth = new DoubleField("rbf width","RBF Width",true,0,1000));
    addProperty(this.cols = new IntegerField("cols", "2D RBF Columns",true,0,1000000));
    addProperty(this.rows = new IntegerField("rows", "2D RBF Rows",true,0,1000000));
    addProperty(this.forceWinner = new CheckField("force winner","Force Winner"));
    render();
    this.learningRate.setValue(0.25);
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    super(EncogWorkBench.getInstance().getMainWindow());
    setSize(400,400);
    setLocation(200,200);
   
    addProperty(this.maxError = new DoubleField("max error",
        "Maximum Error Percent(0-100)", true, 0, 100));
    if( allowKFold ) {
      addProperty(this.kfold = new IntegerField("kfold","Cross Validation KFold (0=none)",true,0,50));
    } else {
      kfold = null;
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    types.add("Fan-In");
   
    this.setCollectCurrentTabOnly(true);
       
    this.beginTab("Randomize");
    addProperty(this.high = new DoubleField("high","High Range",true,0,-1));
    addProperty(this.low = new DoubleField("low","Low Range",true,0,-1));
    addProperty(this.type = new ComboBoxField("type","Type",true,types));
    this.beginTab("Perturb");
    addProperty(this.perturbPercent = new DoubleField("perturb percent","Perturb Percent",true,0,-1));
    this.beginTab("Gaussian");
    addProperty(this.mean = new DoubleField("mean","Mean",true,0,-1));
    addProperty(this.deviation = new DoubleField("standard deviation","Standard Deviation",true,0,-1));
    this.beginTab("Consistent");
    addProperty(this.seedValue = new IntegerField("seed value","Seed Value",true,0,-1));
    addProperty(this.constHigh = new DoubleField("high","High Range",true,0,-1));
    addProperty(this.constLow = new DoubleField("low","Low Range",true,0,-1));   
    this.beginTab("Constant");
    addProperty(this.constantValue = new DoubleField("constant value","Constant Value",true,0,-1));
    render();
  }
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   */
  public InputSVM(SVM svm) {
    super(EncogWorkBench.getInstance().getMainWindow());
    setSize(320,200);
    setTitle("Support Vector Machine (SVM)");
    addProperty(this.gamma = new DoubleField("gamma","Gamma (0 for 1/#input)",true,-1,-1));
    addProperty(this.c = new DoubleField("c","C",true,-1,-1));
    render(); 
    this.c.setValue(1);
    this.gamma.setValue(1.0/svm.getInputCount());
  }
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   */
  public InputADALINE() {
    super(false);
    setTitle("Train ADALINE");
   
    addProperty(this.learningRate = new DoubleField("learning rate","Learning Rate",true,0,-1));
    render();
    this.learningRate.setValue(0.01);
  }
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   * @param owner
   */
  public InputBackpropagation() {
    super(true);
    setTitle("Train Backpropagation");
    addProperty(this.learningRate = new DoubleField("learning rate","Learning Rate",true,-1,-1));
    addProperty(this.momentum = new DoubleField("momentum","Momentum",true,-1,-1));
    render();
    this.learningRate.setValue(0.7);
    this.momentum.setValue(0.0);

    this.getMaxError().setValue(EncogWorkBench.getInstance().getConfig().getDefaultError());
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   */
  public InputInstar() {
    super(false);
    setTitle("Train Instar");

    addProperty(this.learningRate = new DoubleField("learning rate","Learning Rate",true,-1,-1));
    addProperty(this.initWeights = new CheckField("init weights","Init Weights from Training Data"));

    render();
    this.learningRate.setValue(0.7);   
    this.getInitWeights().setValue(true);
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Related Classes of org.encog.workbench.dialogs.common.DoubleField

  • org.encog.workbench.dialogs.config.EncogConfigDialog
  • org.encog.workbench.dialogs.population.EditPopulationDialog
  • org.encog.workbench.dialogs.RandomizeNetworkDialog
  • org.encog.workbench.dialogs.training.DialogMaxError
  • org.encog.workbench.dialogs.training.methods.InputADALINE
  • org.encog.workbench.dialogs.training.methods.InputAnneal
  • org.encog.workbench.dialogs.training.methods.InputBackpropagation
  • org.encog.workbench.dialogs.training.methods.InputGenetic
  • org.encog.workbench.dialogs.training.methods.InputInstar
  • org.encog.workbench.dialogs.training.methods.InputManhattan
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