Package org.apache.spark.ml.feature
Interface RobustScalerParams
- All Superinterfaces:
- HasInputCol,- HasOutputCol,- HasRelativeError,- Identifiable,- Params,- Serializable
- All Known Implementing Classes:
- RobustScaler,- RobustScalerModel
Params for 
RobustScaler and RobustScalerModel.- 
Method SummaryModifier and TypeMethodDescriptiondoublegetLower()doublegetUpper()booleanbooleanlower()Lower quantile to calculate quantile range, shared by all features Default: 0.25upper()Upper quantile to calculate quantile range, shared by all features Default: 0.75validateAndTransformSchema(StructType schema) Validates and transforms the input schema.Whether to center the data with median before scaling.Whether to scale the data to quantile range.Methods inherited from interface org.apache.spark.ml.param.shared.HasInputColgetInputCol, inputColMethods inherited from interface org.apache.spark.ml.param.shared.HasOutputColgetOutputCol, outputColMethods inherited from interface org.apache.spark.ml.param.shared.HasRelativeErrorgetRelativeError, relativeErrorMethods inherited from interface org.apache.spark.ml.util.IdentifiabletoString, uidMethods inherited from interface org.apache.spark.ml.param.Paramsclear, copy, copyValues, defaultCopy, defaultParamMap, estimateMatadataSize, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
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Method Details- 
getLowerdouble getLower()
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getUpperdouble getUpper()
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getWithCenteringboolean getWithCentering()
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getWithScalingboolean getWithScaling()
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lowerDoubleParam lower()Lower quantile to calculate quantile range, shared by all features Default: 0.25- Returns:
- (undocumented)
 
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upperDoubleParam upper()Upper quantile to calculate quantile range, shared by all features Default: 0.75- Returns:
- (undocumented)
 
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validateAndTransformSchemaValidates and transforms the input schema.
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withCenteringBooleanParam withCentering()Whether to center the data with median before scaling. It will build a dense output, so take care when applying to sparse input. Default: false- Returns:
- (undocumented)
 
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withScalingBooleanParam withScaling()Whether to scale the data to quantile range. Default: true- Returns:
- (undocumented)
 
 
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