org.apache.spark.ml.classification

Class ClassificationModel<FeaturesType,M extends ClassificationModel<FeaturesType,M>>

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

org.apache.spark.ml.Model<M>

org.apache.spark.ml.PredictionModel<FeaturesType,M>

org.apache.spark.ml.classification.ClassificationModel<FeaturesType,M>

All Implemented Interfaces:

java.io.Serializable, Params, Identifiable

Direct Known Subclasses:

ProbabilisticClassificationModel

public abstract class ClassificationModel<FeaturesType,M extends ClassificationModel<FeaturesType,M>>
extends PredictionModel<FeaturesType,M>

:: DeveloperApi ::

Model produced by a Classifier. Classes are indexed {0, 1, ..., numClasses - 1}.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
ClassificationModel()

Method Summary

Methods

Modifier and Type	Method and Description
Param<String>	featuresCol() Param for features column name.
String	getFeaturesCol()
String	getLabelCol()
String	getPredictionCol()
String	getRawPredictionCol()
Param<String>	labelCol() Param for label column name.
abstract int	numClasses() Number of classes (values which the label can take).
Param<String>	predictionCol() Param for prediction column name.
Param<String>	rawPredictionCol() Param for raw prediction (a.k.a.
M	setRawPredictionCol(String value)
Dataset<Row>	transform(Dataset<?> dataset) Transforms dataset by reading from featuresCol, and appending new columns as specified by parameters: - predicted labels as predictionCol of type Double - raw predictions (confidences) as rawPredictionCol of type Vector.
StructType	validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType)
StructType	validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType) Validates and transforms the input schema with the provided param map.

Methods inherited from class org.apache.spark.ml.PredictionModel

numFeatures, setFeaturesCol, setPredictionCol, transformSchema

Methods inherited from class org.apache.spark.ml.Model

copy, hasParent, parent, setParent

Methods inherited from class org.apache.spark.ml.Transformer

transform, transform, transform

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.spark.ml.param.Params

clear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Methods inherited from interface org.apache.spark.ml.util.Identifiable

toString, uid

Constructor Detail

ClassificationModel

public ClassificationModel()

Method Detail

setRawPredictionCol

public M setRawPredictionCol(String value)

numClasses

public abstract int numClasses()

Number of classes (values which the label can take).

transform

public Dataset<Row> transform(Dataset<?> dataset)

Transforms dataset by reading from featuresCol, and appending new columns as specified by parameters: - predicted labels as predictionCol of type Double - raw predictions (confidences) as rawPredictionCol of type Vector.

Overrides:

transform in class PredictionModel<FeaturesType,M extends ClassificationModel<FeaturesType,M>>

Parameters:

dataset - input dataset

Returns:

transformed dataset

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema,
                                    boolean fitting,
                                    DataType featuresDataType)

rawPredictionCol

public Param<String> rawPredictionCol()

Param for raw prediction (a.k.a. confidence) column name.

Returns:

(undocumented)

getRawPredictionCol

public String getRawPredictionCol()

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema,
                                    boolean fitting,
                                    DataType featuresDataType)

Validates and transforms the input schema with the provided param map.

Parameters:

schema - input schema

fitting - whether this is in fitting

featuresDataType - SQL DataType for FeaturesType. E.g., VectorUDT for vector features.

Returns:

output schema

labelCol

public Param<String> labelCol()

Param for label column name.

Returns:

(undocumented)

getLabelCol

public String getLabelCol()

featuresCol

public Param<String> featuresCol()

Param for features column name.

Returns:

(undocumented)

getFeaturesCol

public String getFeaturesCol()

predictionCol

public Param<String> predictionCol()

Param for prediction column name.

Returns:

(undocumented)

getPredictionCol

public String getPredictionCol()