Examples of addRegressionTable()

Examples of cascading.pattern.model.generalregression.GeneralRegressionSpec.addRegressionTable()

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    GeneralRegressionSpec regressionSpec = new GeneralRegressionSpec( modelSchema );

    regressionSpec.setNormalization( RegressionUtil.getNormalizationMethod( model ) );

    for( org.dmg.pmml.RegressionTable regressionTable : model.getRegressionTables() )
      regressionSpec.addRegressionTable( RegressionUtil.createTable( regressionTable ) );

    return create( tail, modelSchema, new CategoricalRegressionFunction( regressionSpec ) );
    }

  private Pipe handlePredictionRegressionModel( Pipe tail, RegressionModel model )
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Examples of cascading.pattern.model.generalregression.GeneralRegressionSpec.addRegressionTable()

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    GeneralRegressionSpec regressionSpec = new GeneralRegressionSpec( modelSchema );

    regressionSpec.setLinkFunction( LinkFunction.NONE );

    regressionSpec.addRegressionTable( RegressionUtil.createTable( regressionTable ) );

    return create( tail, modelSchema, new PredictionRegressionFunction( regressionSpec ) );
    }

  private Pipe handleClusteringModel( Pipe tail, ClusteringModel model )
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Examples of cascading.pattern.model.generalregression.GeneralRegressionSpec.addRegressionTable()

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    table.addParameter( new Parameter( "p1", 11.7592159418536d, new CovariantPredictor( "sepal_length" ) ) );
    table.addParameter( new Parameter( "p2", 7.84157781514097d, new CovariantPredictor( "sepal_width" ) ) );
    table.addParameter( new Parameter( "p3", -20.0880078273996d, new CovariantPredictor( "petal_length" ) ) );
    table.addParameter( new Parameter( "p4", -21.6076488529538d, new CovariantPredictor( "petal_width" ) ) );

    regressionSpec.addRegressionTable( table );

    PredictionRegressionFunction regressionFunction = new PredictionRegressionFunction( regressionSpec );

    TupleEntry tupleArguments = new TupleEntry( expectedFields, new Tuple( 5.1d, 3.8d, 1.6d, 0.2d ) );
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Examples of cascading.pattern.model.generalregression.GeneralRegressionSpec.addRegressionTable()

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    regressionTable.addParameter( new Parameter( "p4", 0d, new FactorPredictor( "species", "setosa" ) ) );
    regressionTable.addParameter( new Parameter( "p5", -0.43150751368126d, new FactorPredictor( "species", "versicolor" ) ) );
    regressionTable.addParameter( new Parameter( "p6", -0.61868924203063d, new FactorPredictor( "species", "virginica" ) ) );

    regressionSpec.addRegressionTable( regressionTable );

    PredictionRegressionFunction regressionFunction = new PredictionRegressionFunction( regressionSpec );

    TupleEntry tupleArguments = new TupleEntry( expectedFields, new Tuple( 3d, 1.3d, 0.2d, "setosa" ) );
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Examples of cascading.pattern.model.generalregression.GeneralRegressionSpec.addRegressionTable()

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    regressionTable.addParameter( new Parameter( "p0", -11.3336819785783d, new CovariantPredictor( "sepal_length" ) ) );
    regressionTable.addParameter( new Parameter( "p1", -40.8601511206805d, new CovariantPredictor( "sepal_width" ) ) );
    regressionTable.addParameter( new Parameter( "p2", 38.439099544679d, new CovariantPredictor( "petal_length" ) ) );
    regressionTable.addParameter( new Parameter( "p3", -12.2920287460217d, new CovariantPredictor( "petal_width" ) ) );

    regressionSpec.addRegressionTable( regressionTable );
    }

    {
    RegressionTable regressionTable = new RegressionTable( "virginica" );
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Examples of cascading.pattern.model.generalregression.GeneralRegressionSpec.addRegressionTable()

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    regressionTable.addParameter( new Parameter( "p0", -47.1170644419116d, new CovariantPredictor( "sepal_length" ) ) );
    regressionTable.addParameter( new Parameter( "p1", -51.6805606658275d, new CovariantPredictor( "sepal_width" ) ) );
    regressionTable.addParameter( new Parameter( "p2", 108.27736751831d, new CovariantPredictor( "petal_length" ) ) );
    regressionTable.addParameter( new Parameter( "p3", 54.0277175236148d, new CovariantPredictor( "petal_width" ) ) );

    regressionSpec.addRegressionTable( regressionTable );
    }

    {
    RegressionTable regressionTable = new RegressionTable( "setosa" );
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Examples of cascading.pattern.model.generalregression.GeneralRegressionSpec.addRegressionTable()

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    {
    RegressionTable regressionTable = new RegressionTable( "setosa" );

    regressionTable.addParameter( new Parameter( "intercept", 0d ) );

    regressionSpec.addRegressionTable( regressionTable );
    }

    CategoricalRegressionFunction regressionFunction = new CategoricalRegressionFunction( regressionSpec );

    {
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