org.apache.spark.ml.feature

Class OneHotEncoderModel

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

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

org.apache.spark.ml.feature.OneHotEncoderModel

All Implemented Interfaces:

java.io.Serializable, org.apache.spark.internal.Logging, OneHotEncoderBase, Params, HasHandleInvalid, HasInputCol, HasInputCols, HasOutputCol, HasOutputCols, Identifiable, MLWritable

public class OneHotEncoderModel
extends Model<OneHotEncoderModel>
implements OneHotEncoderBase, MLWritable

param: categorySizes Original number of categories for each feature being encoded. The array contains one value for each input column, in order.

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

org.apache.spark.internal.Logging.SparkShellLoggingFilter

Method Summary

Modifier and Type	Method and Description
int[]	categorySizes()
OneHotEncoderModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
BooleanParam	dropLast() Whether to drop the last category in the encoded vector (default: true)
Param<String>	handleInvalid() Param for how to handle invalid data during transform().
Param<String>	inputCol() Param for input column name.
StringArrayParam	inputCols() Param for input column names.
static OneHotEncoderModel	load(String path)
Param<String>	outputCol() Param for output column name.
StringArrayParam	outputCols() Param for output column names.
static MLReader<OneHotEncoderModel>	read()
OneHotEncoderModel	setDropLast(boolean value)
OneHotEncoderModel	setHandleInvalid(String value)
OneHotEncoderModel	setInputCol(String value)
OneHotEncoderModel	setInputCols(String[] values)
OneHotEncoderModel	setOutputCol(String value)
OneHotEncoderModel	setOutputCols(String[] values)
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.
MLWriter	write() Returns an MLWriter instance for this ML instance.

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

params

Methods inherited from class Object

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

Methods inherited from interface org.apache.spark.ml.feature.OneHotEncoderBase

getDropLast, getInOutCols, validateAndTransformSchema

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

getHandleInvalid

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

getInputCol

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

getInputCols

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

getOutputCol

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, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

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

Method Detail

read

public static MLReader<OneHotEncoderModel> read()

load

public static OneHotEncoderModel load(String path)

handleInvalid

public Param<String> handleInvalid()

Description copied from interface: OneHotEncoderBase

Param for how to handle invalid data during transform(). Options are 'keep' (invalid data presented as an extra categorical feature) or 'error' (throw an error). Note that this Param is only used during transform; during fitting, invalid data will result in an error. Default: "error"

Specified by:

handleInvalid in interface OneHotEncoderBase

Specified by:

handleInvalid in interface HasHandleInvalid

Returns:

(undocumented)

dropLast

public final BooleanParam dropLast()

Description copied from interface: OneHotEncoderBase

Whether to drop the last category in the encoded vector (default: true)

Specified by:

dropLast in interface OneHotEncoderBase

Returns:

(undocumented)

outputCols

public final StringArrayParam outputCols()

Description copied from interface: HasOutputCols

Param for output column names.

Specified by:

outputCols in interface HasOutputCols

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)

inputCols

public final StringArrayParam inputCols()

Description copied from interface: HasInputCols

Param for input column names.

Specified by:

inputCols in interface HasInputCols

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)

categorySizes

public int[] categorySizes()

setInputCol

public OneHotEncoderModel setInputCol(String value)

setOutputCol

public OneHotEncoderModel setOutputCol(String value)

setInputCols

public OneHotEncoderModel setInputCols(String[] values)

setOutputCols

public OneHotEncoderModel setOutputCols(String[] values)

setDropLast

public OneHotEncoderModel setDropLast(boolean value)

setHandleInvalid

public OneHotEncoderModel setHandleInvalid(String value)

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)

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)

copy

public OneHotEncoderModel 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<OneHotEncoderModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

write

public MLWriter write()

Description copied from interface: MLWritable

Returns an MLWriter instance for this ML instance.

Specified by:

write in interface MLWritable

Returns:

(undocumented)

toString

public String toString()

Specified by:

toString in interface Identifiable

Overrides:

toString in class Object