PredictionModel#

classpyspark.ml.PredictionModel[source]#

Model for prediction tasks (regression and classification).

Methods

clear(param)	Clears a param from the param map if it has been explicitly set.
copy([extra])	Creates a copy of this instance with the same uid and some extra params.
explainParam(param)	Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.
explainParams()	Returns the documentation of all params with their optionally default values and user-supplied values.
extractParamMap([extra])	Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values < user-supplied values < extra.
getFeaturesCol()	Gets the value of featuresCol or its default value.
getLabelCol()	Gets the value of labelCol or its default value.
getOrDefault(param)	Gets the value of a param in the user-supplied param map or its default value.
getParam(paramName)	Gets a param by its name.
getPredictionCol()	Gets the value of predictionCol or its default value.
hasDefault(param)	Checks whether a param has a default value.
hasParam(paramName)	Tests whether this instance contains a param with a given (string) name.
isDefined(param)	Checks whether a param is explicitly set by user or has a default value.
isSet(param)	Checks whether a param is explicitly set by user.
predict(value)	Predict label for the given features.
set(param, value)	Sets a parameter in the embedded param map.
setFeaturesCol(value)	Sets the value offeaturesCol.
setPredictionCol(value)	Sets the value ofpredictionCol.
transform(dataset[, params])	Transforms the input dataset with optional parameters.

Attributes

featuresCol
labelCol
numFeatures	Returns the number of features the model was trained on.
params	Returns all params ordered by name.
predictionCol

Methods Documentation

clear(param)#

Clears a param from the param map if it has been explicitly set.

copy(extra=None)#

Creates a copy of this instance with the same uid and someextra params. The default implementation creates ashallow copy usingcopy.copy(), and then copies theembedded and extra parameters over and returns the copy.Subclasses should override this method if the default approachis not sufficient.

Parameters

extradict, optional

Extra parameters to copy to the new instance

Returns

Params

Copy of this instance

explainParam(param)#

Explains a single param and returns its name, doc, and optionaldefault value and user-supplied value in a string.

explainParams()#

Returns the documentation of all params with their optionallydefault values and user-supplied values.

extractParamMap(extra=None)#

Extracts the embedded default param values and user-suppliedvalues, and then merges them with extra values from input intoa flat param map, where the latter value is used if there existconflicts, i.e., with ordering: default param values <user-supplied values < extra.

Parameters

extradict, optional

extra param values

Returns

dict

merged param map

getFeaturesCol()#

Gets the value of featuresCol or its default value.

getLabelCol()#

Gets the value of labelCol or its default value.

getOrDefault(param)#

Gets the value of a param in the user-supplied param map or itsdefault value. Raises an error if neither is set.

getParam(paramName)#

Gets a param by its name.

getPredictionCol()#

Gets the value of predictionCol or its default value.

hasDefault(param)#

Checks whether a param has a default value.

hasParam(paramName)#

Tests whether this instance contains a param with a given(string) name.

isDefined(param)#

Checks whether a param is explicitly set by user or hasa default value.

isSet(param)#

Checks whether a param is explicitly set by user.

abstractpredict(value)[source]#

Predict label for the given features.

New in version 3.0.0.

set(param,value)#

Sets a parameter in the embedded param map.

setFeaturesCol(value)[source]#

Sets the value offeaturesCol.

New in version 3.0.0.

setPredictionCol(value)[source]#

Sets the value ofpredictionCol.

New in version 3.0.0.

transform(dataset,params=None)#

Transforms the input dataset with optional parameters.

New in version 1.3.0.

Parameters

datasetpyspark.sql.DataFrame

input dataset

paramsdict, optional

an optional param map that overrides embedded params.

Returns

pyspark.sql.DataFrame

transformed dataset

Attributes Documentation

featuresCol=Param(parent='undefined',name='featuresCol',doc='featurescolumnname.')#

labelCol=Param(parent='undefined',name='labelCol',doc='labelcolumnname.')#

numFeatures#

Returns the number of features the model was trained on. If unknown, returns -1

New in version 2.1.0.

params#

Returns all params ordered by name. The default implementationusesdir() to get all attributes of typeParam.

predictionCol=Param(parent='undefined',name='predictionCol',doc='predictioncolumnname.')#

uid#

A unique id for the object.