org.apache.spark.ml.feature

Class Bucketizer

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

org.apache.spark.ml.Model<Bucketizer>

org.apache.spark.ml.feature.Bucketizer

All Implemented Interfaces:

java.io.Serializable, Logging, Params, HasHandleInvalid, HasInputCol, HasInputCols, HasOutputCol, HasOutputCols, DefaultParamsWritable, Identifiable, MLWritable

public final class Bucketizer
extends Model<Bucketizer>
implements HasHandleInvalid, HasInputCol, HasOutputCol, HasInputCols, HasOutputCols, DefaultParamsWritable

Bucketizer maps a column of continuous features to a column of feature buckets.

Since 2.3.0, Bucketizer 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 splits parameter is only used for single column usage, and splitsArray is for multiple columns.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
Bucketizer()
Bucketizer(String uid)

Method Summary

Modifier and Type	Method and Description
static Params	clear(Param<?> param)
Bucketizer	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
static String	explainParam(Param<?> param)
static String	explainParams()
static ParamMap	extractParamMap()
static ParamMap	extractParamMap(ParamMap extra)
static <T> scala.Option<T>	get(Param<T> param)
static <T> scala.Option<T>	getDefault(Param<T> param)
static String	getHandleInvalid()
static String	getInputCol()
static String[]	getInputCols()
static <T> T	getOrDefault(Param<T> param)
static String	getOutputCol()
static String[]	getOutputCols()
static Param<Object>	getParam(String paramName)
double[]	getSplits()
double[][]	getSplitsArray()
Param<String>	handleInvalid() Param for how to handle invalid entries.
static <T> boolean	hasDefault(Param<T> param)
static boolean	hasParam(String paramName)
static boolean	hasParent()
static Param<String>	inputCol()
static StringArrayParam	inputCols()
static boolean	isDefined(Param<?> param)
static boolean	isSet(Param<?> param)
static Bucketizer	load(String path)
static Param<String>	outputCol()
static StringArrayParam	outputCols()
static Param<?>[]	params()
static void	parent_$eq(Estimator<M> x$1)
static Estimator<M>	parent()
static void	save(String path)
static <T> Params	set(Param<T> param, T value)
Bucketizer	setHandleInvalid(String value)
Bucketizer	setInputCol(String value)
Bucketizer	setInputCols(String[] value)
Bucketizer	setOutputCol(String value)
Bucketizer	setOutputCols(String[] value)
static M	setParent(Estimator<M> parent)
Bucketizer	setSplits(double[] value)
Bucketizer	setSplitsArray(double[][] value)
DoubleArrayParam	splits() Parameter for mapping continuous features into buckets.
DoubleArrayArrayParam	splitsArray() Parameter for specifying multiple splits parameters.
static String	toString()
Dataset<Row>	transform(Dataset<?> dataset) Transforms the input dataset.
StructType	transformSchema(StructType schema) :: DeveloperApi ::
String	uid() An immutable unique ID for the object and its derivatives.
static MLWriter	write()

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

hasParent, parent, setParent

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

transform, transform, transform

Methods inherited from class Object

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

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

getHandleInvalid

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

getInputCol, inputCol

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

getOutputCol, outputCol

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

getInputCols, inputCols

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

getOutputCols, outputCols

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

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

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

Constructor Detail

Bucketizer

public Bucketizer(String uid)

Bucketizer

public Bucketizer()

Method Detail

load

public static Bucketizer load(String path)

toString

public static String toString()

params

public static Param<?>[] params()

explainParam

public static String explainParam(Param<?> param)

explainParams

public static String explainParams()

isSet

public static final boolean isSet(Param<?> param)

isDefined

public static final boolean isDefined(Param<?> param)

hasParam

public static boolean hasParam(String paramName)

getParam

public static Param<Object> getParam(String paramName)

set

public static final <T> Params set(Param<T> param,
                                   T value)

get

public static final <T> scala.Option<T> get(Param<T> param)

clear

public static final Params clear(Param<?> param)

getOrDefault

public static final <T> T getOrDefault(Param<T> param)

getDefault

public static final <T> scala.Option<T> getDefault(Param<T> param)

hasDefault

public static final <T> boolean hasDefault(Param<T> param)

extractParamMap

public static final ParamMap extractParamMap(ParamMap extra)

extractParamMap

public static final ParamMap extractParamMap()

parent

public static Estimator<M> parent()

parent_$eq

public static void parent_$eq(Estimator<M> x$1)

setParent

public static M setParent(Estimator<M> parent)

hasParent

public static boolean hasParent()

getHandleInvalid

public static final String getHandleInvalid()

inputCol

public static final Param<String> inputCol()

getInputCol

public static final String getInputCol()

outputCol

public static final Param<String> outputCol()

getOutputCol

public static final String getOutputCol()

inputCols

public static final StringArrayParam inputCols()

getInputCols

public static final String[] getInputCols()

outputCols

public static final StringArrayParam outputCols()

getOutputCols

public static final String[] getOutputCols()

save

public static void save(String path)
                 throws java.io.IOException

Throws:

java.io.IOException

write

public static MLWriter write()

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)

splits

public DoubleArrayParam splits()

Parameter for mapping continuous features into buckets. With n+1 splits, there are n buckets. A bucket defined by splits x,y holds values in the range [x,y) except the last bucket, which also includes y. Splits should be of length greater than or equal to 3 and strictly increasing. Values at -inf, inf must be explicitly provided to cover all Double values; otherwise, values outside the splits specified will be treated as errors.

See also handleInvalid, which can optionally create an additional bucket for NaN values.

Returns:

(undocumented)

getSplits

public double[] getSplits()

setSplits

public Bucketizer setSplits(double[] value)

setInputCol

public Bucketizer setInputCol(String value)

setOutputCol

public Bucketizer setOutputCol(String value)

handleInvalid

public Param<String> handleInvalid()

Param for how to handle invalid entries. Options are 'skip' (filter out rows with invalid values), 'error' (throw an error), or 'keep' (keep invalid values in a special additional bucket). Note that in the multiple column case, the invalid handling is applied to all columns. That said for 'error' it will throw an error if any invalids are found in any column, for 'skip' it will skip rows with any invalids in any columns, etc. Default: "error"

Specified by:

handleInvalid in interface HasHandleInvalid

Returns:

(undocumented)

setHandleInvalid

public Bucketizer setHandleInvalid(String value)

splitsArray

public DoubleArrayArrayParam splitsArray()

Parameter for specifying multiple splits parameters. Each element in this array can be used to map continuous features into buckets.

Returns:

(undocumented)

getSplitsArray

public double[][] getSplitsArray()

setSplitsArray

public Bucketizer setSplitsArray(double[][] value)

setInputCols

public Bucketizer setInputCols(String[] value)

setOutputCols

public Bucketizer 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

:: 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)

copy

public Bucketizer 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 Model<Bucketizer>

Parameters:

extra - (undocumented)

Returns:

(undocumented)