Package org.apache.spark.ml.param.shared

Interface HasStandardization

All Superinterfaces:

Identifiable, Params, Serializable

All Known Subinterfaces:

LinearRegressionParams, LinearSVCParams, LogisticRegressionParams

All Known Implementing Classes:

LinearRegression, LinearRegressionModel, LinearSVC, LinearSVCModel, LogisticRegression, LogisticRegressionModel

public interface HasStandardization
extends Params

Trait for shared param standardization (default: true). This trait may be changed or removed between minor versions.

Method Summary

Modifier and Type	Method	Description
boolean	getStandardization()
BooleanParam	standardization()	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, estimateMatadataSize, 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)