public class UnivariateFeatureSelectorModel extends Model<UnivariateFeatureSelectorModel> implements UnivariateFeatureSelectorParams, MLWritable
UnivariateFeatureSelectorModel.| Modifier and Type | Method and Description |
|---|---|
UnivariateFeatureSelectorModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
Param<String> |
featuresCol()
Param for features column name.
|
Param<String> |
featureType()
The feature type.
|
Param<String> |
labelCol()
Param for label column name.
|
Param<String> |
labelType()
The label type.
|
static UnivariateFeatureSelectorModel |
load(String path) |
Param<String> |
outputCol()
Param for output column name.
|
static MLReader<UnivariateFeatureSelectorModel> |
read() |
int[] |
selectedFeatures() |
Param<String> |
selectionMode()
The selection mode.
|
DoubleParam |
selectionThreshold()
The upper bound of the features that selector will select.
|
UnivariateFeatureSelectorModel |
setFeaturesCol(String value) |
UnivariateFeatureSelectorModel |
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.
|
MLWriter |
write()
Returns an
MLWriter instance for this ML instance. |
transform, transform, transformparamsgetFeatureType, getLabelType, getSelectionMode, getSelectionThresholdgetFeaturesColgetLabelColgetOutputColclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwnsave$init$, 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_, uninitializepublic static MLReader<UnivariateFeatureSelectorModel> read()
public static UnivariateFeatureSelectorModel load(String path)
public final Param<String> featureType()
UnivariateFeatureSelectorParamsfeatureType in interface UnivariateFeatureSelectorParamspublic final Param<String> labelType()
UnivariateFeatureSelectorParamslabelType in interface UnivariateFeatureSelectorParamspublic final Param<String> selectionMode()
UnivariateFeatureSelectorParamsselectionMode in interface UnivariateFeatureSelectorParamspublic final DoubleParam selectionThreshold()
UnivariateFeatureSelectorParamsselectionThreshold in interface UnivariateFeatureSelectorParamspublic final Param<String> outputCol()
HasOutputColoutputCol in interface HasOutputColpublic final Param<String> labelCol()
HasLabelCollabelCol in interface HasLabelColpublic final Param<String> featuresCol()
HasFeaturesColfeaturesCol in interface HasFeaturesColpublic String uid()
Identifiableuid in interface Identifiablepublic int[] selectedFeatures()
public UnivariateFeatureSelectorModel setFeaturesCol(String value)
public UnivariateFeatureSelectorModel setOutputCol(String value)
public Dataset<Row> transform(Dataset<?> dataset)
Transformertransform in class Transformerdataset - (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
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.
transformSchema in class PipelineStageschema - (undocumented)public UnivariateFeatureSelectorModel copy(ParamMap extra)
ParamsdefaultCopy().copy in interface Paramscopy in class Model<UnivariateFeatureSelectorModel>extra - (undocumented)public MLWriter write()
MLWritableMLWriter instance for this ML instance.write in interface MLWritablepublic String toString()
toString in interface IdentifiabletoString in class Object