org.apache.spark.ml

Class Predictor<FeaturesType,Learner extends Predictor<FeaturesType,Learner,M>,M extends PredictionModel<FeaturesType,M>>

Object

org.apache.spark.ml.PipelineStage

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

org.apache.spark.ml.Predictor<FeaturesType,Learner,M>

All Implemented Interfaces:

java.io.Serializable, Params, Identifiable

Direct Known Subclasses:

Classifier, DecisionTreeRegressor, GBTClassifier, GBTRegressor, GeneralizedLinearRegression, LinearRegression, MultilayerPerceptronClassifier, RandomForestRegressor

public abstract class Predictor<FeaturesType,Learner extends Predictor<FeaturesType,Learner,M>,M extends PredictionModel<FeaturesType,M>>
extends Estimator<M>

:: DeveloperApi :: Abstraction for prediction problems (regression and classification). It accepts all NumericType labels and will automatically cast it to DoubleType in fit().

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
Predictor()

Method Summary

Methods

Modifier and Type	Method and Description
abstract Learner	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
Param<String>	featuresCol() Param for features column name.
M	fit(Dataset<?> dataset) Fits a model to the input data.
String	getFeaturesCol()
String	getLabelCol()
String	getPredictionCol()
Param<String>	labelCol() Param for label column name.
Param<String>	predictionCol() Param for prediction column name.
Learner	setFeaturesCol(String value)
Learner	setLabelCol(String value)
Learner	setPredictionCol(String value)
StructType	transformSchema(StructType schema) :: DeveloperApi ::
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.Estimator

fit, fit, fit, fit

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, 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

Predictor

public Predictor()

Method Detail

setLabelCol

public Learner setLabelCol(String value)

setFeaturesCol

public Learner setFeaturesCol(String value)

setPredictionCol

public Learner setPredictionCol(String value)

fit

public M fit(Dataset<?> dataset)

Description copied from class: Estimator

Fits a model to the input data.

Specified by:

fit in class Estimator<M extends PredictionModel<FeaturesType,M>>

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

copy

public abstract Learner copy(ParamMap extra)

Description copied from interface: Params

Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy().

Specified by:

copy in interface Params

Specified by:

copy in class Estimator<M extends PredictionModel<FeaturesType,M>>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

transformSchema

public StructType transformSchema(StructType schema)

Description copied from class: PipelineStage

:: DeveloperApi ::

Check transform validity and derive the output schema from the input schema.

We check validity for interactions between parameters during transformSchema and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled by Param.validate().

Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.

Specified by:

transformSchema in class PipelineStage

Parameters:

schema - (undocumented)

Returns:

(undocumented)

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()