Package cascading.pattern.datafield

Examples of cascading.pattern.datafield.DataField

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    if( predicate instanceof SimplePredicate )
      {
      String fieldName = ( (SimplePredicate) predicate ).getField().getValue();
      String value = ( (SimplePredicate) predicate ).getValue();
      SimplePredicate.Operator operator = ( (SimplePredicate) predicate ).getOperator();
      DataField expectedField = modelSchema.getExpectedField( fieldName );

      if( expectedField == null )
        throw new IllegalStateException( "missing field declaration in dictionary for: " + fieldName );

      Type expectedFieldType = expectedField.getType();

      switch( operator )
        {
        case EQUAL:
          return new EqualsToPredicate( fieldName, Coercions.coerce( value, expectedFieldType ) );
        case NOT_EQUAL:
          return new NotEqualsToPredicate( fieldName, Coercions.coerce( value, expectedFieldType ) );
        case LESS_THAN:
          return new LessThanPredicate( fieldName, (Comparable) Coercions.coerce( value, expectedFieldType ) );
        case LESS_OR_EQUAL:
          return new LessOrEqualThanPredicate( fieldName, (Comparable) Coercions.coerce( value, expectedFieldType ) );
        case GREATER_THAN:
          return new GreaterThanPredicate( fieldName, (Comparable) Coercions.coerce( value, expectedFieldType ) );
        case GREATER_OR_EQUAL:
          return new GreaterOrEqualThanPredicate( fieldName, (Comparable) Coercions.coerce( value, expectedFieldType ) );
        case IS_MISSING:
          return new IsMissingPredicate( fieldName );
        case IS_NOT_MISSING:
          return new IsNotMissingPredicate( fieldName );
        }
      }

    if( predicate instanceof SimpleSetPredicate )
      {
      String fieldName = ( (SimpleSetPredicate) predicate ).getField().getValue();
      Array valueArray = ( (SimpleSetPredicate) predicate ).getArray();
      SimpleSetPredicate.BooleanOperator operator = ( (SimpleSetPredicate) predicate ).getBooleanOperator();
      DataField expectedField = modelSchema.getExpectedField( fieldName );

      if( expectedField == null )
        throw new IllegalStateException( "missing field declaration in dictionary for: " + fieldName );

      List list = PMMLUtil.parseArray( valueArray ); // performs coercions
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    return modelSchema;
    }

  public boolean isPredictedCategorical()
    {
    DataField predictedField = getModelSchema().getPredictedField( getModelSchema().getPredictedFieldNames().get( 0 ) );

    return predictedField instanceof CategoricalDataField;
    }
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    return predictedField instanceof CategoricalDataField;
    }

  public List<String> getCategories()
    {
    DataField predictedField = getModelSchema().getPredictedField( getModelSchema().getPredictedFieldNames().get( 0 ) );

    List<String> categories = new ArrayList<String>();

    if( predictedField instanceof CategoricalDataField )
      categories.addAll( ( (CategoricalDataField) predictedField ).getCategories() );
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  public void setPredictedCategories( String fieldName, String... categories )
    {
    if( !predictedFields.contains( fieldName ) )
      throw new IllegalArgumentException( "predicted field does not exist: " + fieldName );

    DataField dataField = dictionary.get( fieldName );

    if( dataField instanceof ContinuousDataField )
      dataField = new CategoricalDataField( fieldName, String.class, categories );
    else
      dataField = new CategoricalDataField( (CategoricalDataField) dataField, categories );
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    dictionary.put( fieldName, dataField );
    }

  public List<String> getPredictedCategories( String fieldName )
    {
    DataField dataField = dictionary.get( fieldName );

    if( dataField instanceof ContinuousDataField )
      throw new IllegalArgumentException( "field is not categorical: " + fieldName );

    return Collections.unmodifiableList( ( (CategoricalDataField) dataField ).getCategories() );
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    {
    Fields fields = getPredictedFields();

    if( isIncludePredictedCategories() )
      {
      DataField dataField = dictionary.get( fields.get( 0 ).toString() );

      if( dataField instanceof CategoricalDataField )
        {
        for( String category : ( (CategoricalDataField) dataField ).getCategories() )
          fields = fields.append( new Fields( category, boolean.class ) );
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  public ExpressionEvaluator[] getRegressionTableEvaluators( Fields argumentFields )
    {
    List<RegressionTable> tables = new ArrayList<RegressionTable>( regressionTables );

    final DataField predictedField = getModelSchema().getPredictedField( getModelSchema().getPredictedFieldNames().get( 0 ) );

    // order tables in category order as this is the declared field name order
    if( predictedField instanceof CategoricalDataField )
      {
      Ordering<RegressionTable> ordering = Ordering.natural().onResultOf( new Function<RegressionTable, Comparable>()
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    if( regressionSpec.getNormalization() == null )
      throw new IllegalArgumentException( "normalization may not be null" );

    ModelSchema modelSchema = regressionSpec.getModelSchema();

    DataField predictedField = modelSchema.getPredictedField( modelSchema.getPredictedFieldNames().get( 0 ) );

    if( !( predictedField instanceof CategoricalDataField ) )
      throw new IllegalArgumentException( "predicted field must be categorical" );

    if( ( (CategoricalDataField) predictedField ).getCategories().size() != regressionSpec.getRegressionTables().size() )
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  public ClusterEvaluator[] getClusterEvaluator( Fields argumentFields )
    {
    List<Cluster> sorted = new ArrayList<Cluster>( clusters );

    final DataField predictedField = getModelSchema().getPredictedField( getModelSchema().getPredictedFieldNames().get( 0 ) );

    // order tables in category order as this is the declared field name order
    if( predictedField instanceof CategoricalDataField )
      {
      Ordering<Cluster> ordering = Ordering.natural().onResultOf( new Function<Cluster, Comparable>()
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Related Classes of cascading.pattern.datafield.DataField

  • cascading.pattern.model.clustering.ClusteringSpec
  • cascading.pattern.model.generalregression.CategoricalRegressionFunction
  • cascading.pattern.model.generalregression.GeneralRegressionSpec
  • cascading.pattern.model.ModelSchema
  • cascading.pattern.model.Spec
  • cascading.pattern.pmml.TreeUtil
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