org.apache.spark.ml.feature

Class Binarizer

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

org.apache.spark.ml.feature.Binarizer

All Implemented Interfaces:

java.io.Serializable, org.apache.spark.internal.Logging, Params, HasInputCol, HasInputCols, HasOutputCol, HasOutputCols, HasThreshold, HasThresholds, DefaultParamsWritable, Identifiable, MLWritable

public final class Binarizer
extends Transformer
implements HasThreshold, HasThresholds, HasInputCol, HasOutputCol, HasInputCols, HasOutputCols, DefaultParamsWritable

Binarize a column of continuous features given a threshold.

Since 3.0.0, Binarize can map multiple columns at once by setting the inputCols parameter. Note that when both the inputCol and inputCols parameters are set, an Exception will be thrown. The threshold parameter is used for single column usage, and thresholds is for multiple columns.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
Binarizer()
Binarizer(String uid)

Method Summary

Modifier and Type	Method and Description
Binarizer	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
Param<String>	inputCol() Param for input column name.
StringArrayParam	inputCols() Param for input column names.
static Binarizer	load(String path)
Param<String>	outputCol() Param for output column name.
StringArrayParam	outputCols() Param for output column names.
static MLReader<T>	read()
Binarizer	setInputCol(String value)
Binarizer	setInputCols(String[] value)
Binarizer	setOutputCol(String value)
Binarizer	setOutputCols(String[] value)
Binarizer	setThreshold(double value)
Binarizer	setThresholds(double[] value)
DoubleParam	threshold() Param for threshold used to binarize continuous features.
DoubleArrayParam	thresholds() Array of threshold used to binarize continuous features.
String	toString()
Dataset<Row>	transform(Dataset<?> dataset) Transforms the input dataset.
StructType	transformSchema(StructType schema) Check transform validity and derive the output schema from the input schema.
String	uid() An immutable unique ID for the object and its derivatives.

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

transform, transform, transform

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

params

Methods inherited from class Object

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

Methods inherited from interface org.apache.spark.ml.param.shared.HasThreshold

getThreshold

Methods inherited from interface org.apache.spark.ml.param.shared.HasThresholds

getThresholds

Methods inherited from interface org.apache.spark.ml.param.shared.HasInputCol

getInputCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasOutputCol

getOutputCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasInputCols

getInputCols

Methods inherited from interface org.apache.spark.ml.param.shared.HasOutputCols

getOutputCols

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.DefaultParamsWritable

write

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

save

Methods inherited from interface org.apache.spark.internal.Logging

$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize

Constructor Detail

Binarizer

public Binarizer(String uid)

Binarizer

public Binarizer()

Method Detail

load

public static Binarizer load(String path)

read

public static MLReader<T> read()

outputCols

public final StringArrayParam outputCols()

Description copied from interface: HasOutputCols

Param for output column names.

Specified by:

outputCols in interface HasOutputCols

Returns:

(undocumented)

inputCols

public final StringArrayParam inputCols()

Description copied from interface: HasInputCols

Param for input column names.

Specified by:

inputCols in interface HasInputCols

Returns:

(undocumented)

outputCol

public final Param<String> outputCol()

Description copied from interface: HasOutputCol

Param for output column name.

Specified by:

outputCol in interface HasOutputCol

Returns:

(undocumented)

inputCol

public final Param<String> inputCol()

Description copied from interface: HasInputCol

Param for input column name.

Specified by:

inputCol in interface HasInputCol

Returns:

(undocumented)

uid

public String uid()

Description copied from interface: Identifiable

An immutable unique ID for the object and its derivatives.

Specified by:

uid in interface Identifiable

Returns:

(undocumented)

threshold

public DoubleParam threshold()

Param for threshold used to binarize continuous features. The features greater than the threshold, will be binarized to 1.0. The features equal to or less than the threshold, will be binarized to 0.0. Default: 0.0

Specified by:

threshold in interface HasThreshold

Returns:

(undocumented)

setThreshold

public Binarizer setThreshold(double value)

thresholds

public DoubleArrayParam thresholds()

Array of threshold used to binarize continuous features. This is for multiple columns input. If transforming multiple columns and thresholds is not set, but threshold is set, then threshold will be applied across all columns.

Specified by:

thresholds in interface HasThresholds

Returns:

(undocumented)

setThresholds

public Binarizer setThresholds(double[] value)

setInputCol

public Binarizer setInputCol(String value)

setOutputCol

public Binarizer setOutputCol(String value)

setInputCols

public Binarizer setInputCols(String[] value)

setOutputCols

public Binarizer setOutputCols(String[] value)

transform

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

Description copied from class: Transformer

Transforms the input dataset.

Specified by:

transform in class Transformer

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

transformSchema

public StructType transformSchema(StructType schema)

Description copied from class: PipelineStage

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)

copy

public Binarizer 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 Transformer

Parameters:

extra - (undocumented)

Returns:

(undocumented)

toString

public String toString()

Specified by:

toString in interface Identifiable

Overrides:

toString in class Object