Package org.encog.ml.data.versatile.normalizers

Examples of org.encog.ml.data.versatile.normalizers.OneOfNNormalizer

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    ColumnType ct = dataset.getNormHelper().getOutputColumns().get(0).getDataType();
   
    BasicNormalizationStrategy result = new BasicNormalizationStrategy();
    result.assignInputNormalizer(ColumnType.continuous,new RangeNormalizer(0,1));
    result.assignInputNormalizer(ColumnType.nominal,new OneOfNNormalizer(0,1));
    result.assignInputNormalizer(ColumnType.ordinal,new OneOfNNormalizer(0,1));
   
    result.assignOutputNormalizer(ColumnType.continuous,new RangeNormalizer(0,1));
    result.assignOutputNormalizer(ColumnType.nominal,new IndexedNormalizer());
    result.assignOutputNormalizer(ColumnType.ordinal,new OneOfNNormalizer(0,1));
    return result;
  }
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    ColumnType ct = dataset.getNormHelper().getOutputColumns().get(0).getDataType();
   
    BasicNormalizationStrategy result = new BasicNormalizationStrategy();
    result.assignInputNormalizer(ColumnType.continuous,new RangeNormalizer(0,1));
    result.assignInputNormalizer(ColumnType.nominal,new OneOfNNormalizer(0,1));
    result.assignInputNormalizer(ColumnType.ordinal,new OneOfNNormalizer(0,1));
   
    result.assignOutputNormalizer(ColumnType.continuous,new RangeNormalizer(0,1));
    result.assignOutputNormalizer(ColumnType.nominal,new OneOfNNormalizer(0,1));
    result.assignOutputNormalizer(ColumnType.ordinal,new OneOfNNormalizer(0,1));
    return result;
  }
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    ColumnType ct = dataset.getNormHelper().getOutputColumns().get(0).getDataType();
   
    BasicNormalizationStrategy result = new BasicNormalizationStrategy();
    result.assignInputNormalizer(ColumnType.continuous,new RangeNormalizer(0,1));
    result.assignInputNormalizer(ColumnType.nominal,new OneOfNNormalizer(0,1));
    result.assignInputNormalizer(ColumnType.ordinal,new OneOfNNormalizer(0,1));
   
    result.assignOutputNormalizer(ColumnType.continuous,new RangeNormalizer(0,1));
    result.assignOutputNormalizer(ColumnType.nominal,new IndexedNormalizer());
    result.assignOutputNormalizer(ColumnType.ordinal,new OneOfNNormalizer(0,1));
    return result;
  }
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   */
  @Override
  public NormalizationStrategy suggestNormalizationStrategy(VersatileMLDataSet dataset, String architecture) {
    BasicNormalizationStrategy result = new BasicNormalizationStrategy();
    result.assignInputNormalizer(ColumnType.continuous,new RangeNormalizer(0,1));
    result.assignInputNormalizer(ColumnType.nominal,new OneOfNNormalizer(0,1));
    result.assignInputNormalizer(ColumnType.ordinal,new OneOfNNormalizer(0,1));
   
    result.assignOutputNormalizer(ColumnType.continuous,new RangeNormalizer(0,1));
    result.assignOutputNormalizer(ColumnType.nominal,new OneOfNNormalizer(0,1));
    result.assignOutputNormalizer(ColumnType.ordinal,new OneOfNNormalizer(0,1));
    return result;
  }
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   * @param outputLow The desired low to normalize output into.
   * @param outputHigh The desired high to normalize output into.
   */
  public BasicNormalizationStrategy(double inputLow, double inputHigh, double outputLow, double outputHigh) {
    assignInputNormalizer(ColumnType.continuous,new RangeNormalizer(inputLow,inputHigh));
    assignInputNormalizer(ColumnType.nominal,new OneOfNNormalizer(inputLow,inputHigh));
    assignInputNormalizer(ColumnType.ordinal,new RangeOrdinal(inputLow,inputHigh));
   
    assignOutputNormalizer(ColumnType.continuous,new RangeNormalizer(outputLow,outputHigh));
    assignOutputNormalizer(ColumnType.nominal,new OneOfNNormalizer(outputLow,outputHigh));
    assignOutputNormalizer(ColumnType.ordinal,new RangeOrdinal(outputLow,outputHigh));
  }
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Related Classes of org.encog.ml.data.versatile.normalizers.OneOfNNormalizer

  • org.encog.EncogError
  • org.encog.ml.data.versatile.normalizers.strategies.BasicNormalizationStrategy
  • org.encog.ml.model.config.NEATConfig
  • org.encog.ml.model.config.PNNConfig
  • org.encog.ml.model.config.RBFNetworkConfig
  • org.encog.ml.model.config.SVMConfig
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