Examples of org.encog.util.normalize.segregate.index.IndexSampleSegregator

org.encog.util.normalize.segregate.index.IndexSampleSegregator

An index segregator is used to segregate the data according to its index. Nothing about the data is actually compared. This makes the index range segregator very useful for breaking the data into training and validation sets. For example, you could very easily determine that 70% of the data is for training, and 30% for validation. This segregator takes a starting and ending index, as well as a smple size. Everything that is between these two indexes will be used. The sample repeats over and over. For example, if you choose a sample size of 10, and a beginning index of 0 and an ending index of 5, you would get half of the first 10 element, then half of the next ten, and so on.

      norm.setTarget(target);
      norm.addInputField(a = new InputFieldArray2D(false,ARRAY_2D,0));
      norm.addInputField(b = new InputFieldArray2D(false,ARRAY_2D,1));
      norm.addOutputField(new OutputFieldRangeMapped(a,0.1,0.9));
      norm.addOutputField(new OutputFieldRangeMapped(b,0.1,0.9));
      norm.addSegregator(new IndexSampleSegregator(0,3,2));
      return norm;
    }

Examples of org.encog.util.normalize.segregate.index.IndexSampleSegregator

Related Classes of org.encog.util.normalize.segregate.index.IndexSampleSegregator