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, Logging, Params

Direct Known Subclasses:

Classifier, DecisionTreeClassifier, DecisionTreeRegressor, GBTClassifier, GBTRegressor, LinearRegression, RandomForestClassifier, 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).

See Also:

Serialized Form

Constructor Summary

Predictor()

Method Summary

abstract Learner	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
M	fit(DataFrame dataset) Fits a model to the input data.
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, setDefault, shouldOwn, validateParams

Methods inherited from interface org.apache.spark.Logging

initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

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(DataFrame 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.

Specified by:

copy in interface Params

Specified by:

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

Parameters:

extra - (undocumented)

Returns:

(undocumented)

See Also:

defaultCopy()

transformSchema

public StructType transformSchema(StructType schema)

Description copied from class: PipelineStage

:: DeveloperApi ::

Derives the output schema from the input schema.

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