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, transform
params
getFeatureType, getLabelType, getSelectionMode, getSelectionThreshold
getFeaturesCol
getLabelCol
getOutputCol
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
save
$init$, 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
public static MLReader<UnivariateFeatureSelectorModel> read()
public static UnivariateFeatureSelectorModel load(String path)
public final Param<String> featureType()
UnivariateFeatureSelectorParams
featureType
in interface UnivariateFeatureSelectorParams
public final Param<String> labelType()
UnivariateFeatureSelectorParams
labelType
in interface UnivariateFeatureSelectorParams
public final Param<String> selectionMode()
UnivariateFeatureSelectorParams
selectionMode
in interface UnivariateFeatureSelectorParams
public final DoubleParam selectionThreshold()
UnivariateFeatureSelectorParams
selectionThreshold
in interface UnivariateFeatureSelectorParams
public final Param<String> outputCol()
HasOutputCol
outputCol
in interface HasOutputCol
public final Param<String> labelCol()
HasLabelCol
labelCol
in interface HasLabelCol
public final Param<String> featuresCol()
HasFeaturesCol
featuresCol
in interface HasFeaturesCol
public String uid()
Identifiable
uid
in interface Identifiable
public int[] selectedFeatures()
public UnivariateFeatureSelectorModel setFeaturesCol(String value)
public UnivariateFeatureSelectorModel setOutputCol(String value)
public Dataset<Row> transform(Dataset<?> dataset)
Transformer
transform
in class Transformer
dataset
- (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 PipelineStage
schema
- (undocumented)public UnivariateFeatureSelectorModel copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Model<UnivariateFeatureSelectorModel>
extra
- (undocumented)public MLWriter write()
MLWritable
MLWriter
instance for this ML instance.write
in interface MLWritable
public String toString()
toString
in interface Identifiable
toString
in class Object