Package com.greentea.relaxation.jnmf.lib.functions

Examples of com.greentea.relaxation.jnmf.lib.functions.VarSigmoidFunction

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         }

         double absMax = Math.max(Math.abs(averageMin), Math.abs(averageMax));

         selfDescriptiveness.clear();
         VarSigmoidFunction f = new VarSigmoidFunction(-100, 100);
         for (Vector row : rows)
         {
            int averageElementIndex = row.size() - 1;
            double averageValue = (Double) row.get(row.size() - 1);

            for (int i = 1; i < averageElementIndex; ++i)
            {
               double value = (Double) row.get(i);
               double info = f.calc(value);

               row.add(JNMFMathUtils.roundDouble4(info));
            }

            double info = f.calc(averageValue);

            row.add(JNMFMathUtils.roundDouble4(info));
            row.add(JNMFMathUtils.roundDouble4(Math.abs(info)));

            selfDescriptiveness.add(Math.abs(info));
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      builder.setActivationFuncitonFactory(new IFactory<IFunction>()
      {
         public IFunction create()
         {
            return new VarSigmoidFunction();
         }
      });
      for (int i = 0; i < data.getInputsCount(); ++i)
      {
         builder.addDataInputSynapseGenerative(i, 1, i);
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      builder.setActivationFuncitonFactory(new IFactory<IFunction>()
      {
         public IFunction create()
         {
            return new VarSigmoidFunction();
         }
      });
      for (int i = 0; i < data.getInputsCount(); ++i)
      {
         builder.addDataInputSynapseGenerative(i, 1, i);
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      Validate.isTrue(sigmoidMin < sigmoidMax);

      this.sigmoidMin = sigmoidMin;
      this.sigmoidMax = sigmoidMax;

      f = new VarSigmoidFunction(sigmoidMin, sigmoidMax);
   }
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Related Classes of com.greentea.relaxation.jnmf.lib.functions.VarSigmoidFunction

  • com.greentea.relaxation.algorithms.backprop.LogisticRegressionAlgorithm
  • com.greentea.relaxation.algorithms.backprop.MultilayerPerceptronAlgorithm
  • com.greentea.relaxation.jnmf.gui.components.project.network.LogisticRegressionNetworkComponent
  • com.greentea.relaxation.jnmf.lib.functions.deriviative.VarSigmoidDefiviativeFunction
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