How to use

CategoricalRegressionFunction

in

cascading.pattern.model.generalregression

@Override
public void operate( FlowProcess flowProcess, FunctionCall<Context<BaseRegressionFunction.ExpressionContext>> functionCall )
 {
 TupleEntry arguments = functionCall.getArguments();
 ExpressionEvaluator[] expressions = functionCall.getContext().payload.expressions;
 double[] results = functionCall.getContext().payload.results;
 for( int i = 0; i < expressions.length; i++ )
  results[ i ] = expressions[ i ].calculate( arguments );
 LOG.debug( "raw regression: {}", results );
 for( int i = 0; i < expressions.length; i++ )
  results[ i ] = getSpec().getLinkFunction().calculate( results[ i ] );
 LOG.debug( "link regression: {}", results );
 results = getSpec().getNormalization().normalize( results );
 LOG.debug( "probabilities: {}", results );
 double max = Doubles.max( results );
 int index = Doubles.indexOf( results, max );
 String category = expressions[ index ].getTargetCategory();
 LOG.debug( "category: {}", category );
 if( !getSpec().getModelSchema().isIncludePredictedCategories() )
  {
  functionCall.getOutputCollector().add( functionCall.getContext().result( category ) );
  return;
  }
 Tuple result = functionCall.getContext().tuple;
 result.set( 0, category );
 for( int i = 0; i < results.length; i++ )
  result.set( i + 1, results[ i ] );
 functionCall.getOutputCollector().add( result );
 }
}

CategoricalRegressionFunction regressionFunction = new CategoricalRegressionFunction( regressionSpec );