Package org.apache.spark.ml.feature

Class VarianceThresholdSelectorModel

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

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

org.apache.spark.ml.feature.VarianceThresholdSelectorModel

All Implemented Interfaces:

Serializable, org.apache.spark.internal.Logging, VarianceThresholdSelectorParams, Params, HasFeaturesCol, HasOutputCol, Identifiable, MLWritable

public class VarianceThresholdSelectorModel
extends Model<VarianceThresholdSelectorModel>
implements VarianceThresholdSelectorParams, MLWritable

Model fitted by VarianceThresholdSelector.

See Also:

• Serialized Form

Nested Class Summary

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

org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter

Method Summary

Modifier and Type	Method	Description
VarianceThresholdSelectorModel	copy(ParamMap extra)	Creates a copy of this instance with the same UID and some extra params.
final Param<String>	featuresCol()	Param for features column name.
static VarianceThresholdSelectorModel	load(String path)
final Param<String>	outputCol()	Param for output column name.
static MLReader<VarianceThresholdSelectorModel>	read()
int[]	selectedFeatures()
VarianceThresholdSelectorModel	setFeaturesCol(String value)
VarianceThresholdSelectorModel	setOutputCol(String value)
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.
final DoubleParam	varianceThreshold()	Param for variance threshold.
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 java.lang.Object

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

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

getFeaturesCol

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

getOutputCol

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

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

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

save

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.feature.VarianceThresholdSelectorParams

getVarianceThreshold

Method Details

read

public static MLReader<VarianceThresholdSelectorModel> read()

load

public static VarianceThresholdSelectorModel load(String path)

varianceThreshold

public final DoubleParam varianceThreshold()

Description copied from interface: VarianceThresholdSelectorParams

Param for variance threshold. Features with a variance not greater than this threshold will be removed. The default value is 0.0.

Specified by:

varianceThreshold in interface VarianceThresholdSelectorParams

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)

featuresCol

public final Param<String> featuresCol()

Description copied from interface: HasFeaturesCol

Param for features column name.

Specified by:

featuresCol in interface HasFeaturesCol

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)

selectedFeatures

public int[] selectedFeatures()

setFeaturesCol

public VarianceThresholdSelectorModel setFeaturesCol(String value)

setOutputCol

public VarianceThresholdSelectorModel setOutputCol(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 VarianceThresholdSelectorModel 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<VarianceThresholdSelectorModel>

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