org.apache.spark.ml.feature

Class Bucketizer

java.lang.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, Identifiable

public final class Bucketizer
extends Model<Bucketizer>

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

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
Bucketizer()
Bucketizer(java.lang.String uid)

Method Summary

Methods

Modifier and Type	Method and Description
static double	binarySearchForBuckets(double[] splits, double feature) Binary searching in several buckets to place each data point.
static boolean	checkSplits(double[] splits) We require splits to be of length >= 3 and to be in strictly increasing order.
Bucketizer	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
double[]	getSplits()
Bucketizer	setInputCol(java.lang.String value)
Bucketizer	setOutputCol(java.lang.String value)
Bucketizer	setSplits(double[] value)
DoubleArrayParam	splits() Parameter for mapping continuous features into buckets.
DataFrame	transform(DataFrame dataset) Transforms the input dataset.
StructType	transformSchema(StructType schema) :: DeveloperApi ::
java.lang.String	uid() An immutable unique ID for the object and its derivatives.

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 org.apache.spark.ml.PipelineStage

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

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

Bucketizer

public Bucketizer(java.lang.String uid)

Bucketizer

public Bucketizer()

Method Detail

checkSplits

public static boolean checkSplits(double[] splits)

We require splits to be of length >= 3 and to be in strictly increasing order.

binarySearchForBuckets

public static double binarySearchForBuckets(double[] splits,
                            double feature)

Binary searching in several buckets to place each data point.

Parameters:

splits - (undocumented)

feature - (undocumented)

Returns:

(undocumented)

Throws:

SparkException - if a feature is < splits.head or > splits.last

uid

public java.lang.String uid()

Description copied from interface: Identifiable

An immutable unique ID for the object and its derivatives.

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 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.

Returns:

(undocumented)

getSplits

public double[] getSplits()

setSplits

public Bucketizer setSplits(double[] value)

setInputCol

public Bucketizer setInputCol(java.lang.String value)

setOutputCol

public Bucketizer setOutputCol(java.lang.String value)

transform

public DataFrame transform(DataFrame 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 ::

Derives the output schema from the input schema.

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.

Specified by:

copy in interface Params

Specified by:

copy in class Model<Bucketizer>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

See Also:

defaultCopy()