org.apache.spark.ml

Class Estimator<M extends Model<M>>

java.lang.Object

org.apache.spark.ml.PipelineStage

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

All Implemented Interfaces:

java.io.Serializable, Logging, Params, Identifiable

Direct Known Subclasses:

ALS, CountVectorizer, CrossValidator, IDF, IsotonicRegression, KMeans, MinMaxScaler, OneVsRest, PCA, Pipeline, Predictor, RFormula, StandardScaler, StringIndexer, TrainValidationSplit, VectorIndexer, Word2Vec

public abstract class Estimator<M extends Model<M>>
extends PipelineStage

:: DeveloperApi :: Abstract class for estimators that fit models to data.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
Estimator()

Method Summary

Methods

Modifier and Type	Method and Description
abstract Estimator<M>	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
abstract M	fit(DataFrame dataset) Fits a model to the input data.
M	fit(DataFrame dataset, ParamMap paramMap) Fits a single model to the input data with provided parameter map.
scala.collection.Seq<M>	fit(DataFrame dataset, ParamMap[] paramMaps) Fits multiple models to the input data with multiple sets of parameters.
M	fit(DataFrame dataset, ParamPair<?> firstParamPair, ParamPair<?>... otherParamPairs) Fits a single model to the input data with optional parameters.
M	fit(DataFrame dataset, ParamPair<?> firstParamPair, scala.collection.Seq<ParamPair<?>> otherParamPairs) Fits a single model to the input data with optional parameters.

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

transformSchema, transformSchema

Methods inherited from class java.lang.Object

clone, equals, finalize, 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, validateParams

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

toString, uid

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

Estimator

public Estimator()

Method Detail

fit

public M fit(DataFrame dataset,
    ParamPair<?> firstParamPair,
    ParamPair<?>... otherParamPairs)

Fits a single model to the input data with optional parameters.

Parameters:

dataset - input dataset

firstParamPair - the first param pair, overrides embedded params

otherParamPairs - other param pairs. These values override any specified in this Estimator's embedded ParamMap.

Returns:

fitted model

fit

public M fit(DataFrame dataset,
    ParamPair<?> firstParamPair,
    scala.collection.Seq<ParamPair<?>> otherParamPairs)

Fits a single model to the input data with optional parameters.

Parameters:

dataset - input dataset

firstParamPair - the first param pair, overrides embedded params

otherParamPairs - other param pairs. These values override any specified in this Estimator's embedded ParamMap.

Returns:

fitted model

fit

public M fit(DataFrame dataset,
    ParamMap paramMap)

Fits a single model to the input data with provided parameter map.

Parameters:

dataset - input dataset

paramMap - Parameter map. These values override any specified in this Estimator's embedded ParamMap.

Returns:

fitted model

fit

public abstract M fit(DataFrame dataset)

Fits a model to the input data.

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

fit

public scala.collection.Seq<M> fit(DataFrame dataset,
                          ParamMap[] paramMaps)

Fits multiple models to the input data with multiple sets of parameters. The default implementation uses a for loop on each parameter map. Subclasses could override this to optimize multi-model training.

Parameters:

dataset - input dataset

paramMaps - An array of parameter maps. These values override any specified in this Estimator's embedded ParamMap.

Returns:

fitted models, matching the input parameter maps

copy

public abstract Estimator<M> 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 PipelineStage

Parameters:

extra - (undocumented)

Returns:

(undocumented)

See Also:

defaultCopy()