Package org.apache.spark.ml.param.shared
Interface HasStandardization
- All Superinterfaces:
Identifiable
,Params
,Serializable
,scala.Serializable
- All Known Subinterfaces:
LinearRegressionParams
,LinearSVCParams
,LogisticRegressionParams
- All Known Implementing Classes:
LinearRegression
,LinearRegressionModel
,LinearSVC
,LinearSVCModel
,LogisticRegression
,LogisticRegressionModel
Trait for shared param standardization (default: true). This trait may be changed or
removed between minor versions.
-
Method Summary
Modifier and TypeMethodDescriptionboolean
Param for whether to standardize the training features before fitting the model.Methods inherited from interface org.apache.spark.ml.util.Identifiable
toString, uid
Methods inherited from interface org.apache.spark.ml.param.Params
clear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
-
Method Details
-
getStandardization
boolean getStandardization() -
standardization
BooleanParam standardization()Param for whether to standardize the training features before fitting the model.- Returns:
- (undocumented)
-