org.apache.spark.ml.param.shared

Interface HasFeaturesCol

All Superinterfaces:

Identifiable, Params, java.io.Serializable

All Known Subinterfaces:

AFTSurvivalRegressionParams, BisectingKMeansParams, ClassifierParams, DecisionTreeClassifierParams, DecisionTreeParams, DecisionTreeRegressorParams, FactorizationMachines, FactorizationMachinesParams, FMClassifierParams, FMRegressorParams, GaussianMixtureParams, GBTClassifierParams, GBTParams, GBTRegressorParams, GeneralizedLinearRegressionBase, IsotonicRegressionBase, KMeansParams, LDAParams, LinearRegressionParams, LinearSVCParams, LogisticRegressionParams, MultilayerPerceptronParams, NaiveBayesParams, OneVsRestParams, PredictorParams, ProbabilisticClassifierParams, RandomForestClassifierParams, RandomForestParams, RandomForestRegressorParams, RFormulaBase, SelectorParams, TreeEnsembleClassifierParams, TreeEnsembleParams, TreeEnsembleRegressorParams, UnivariateFeatureSelectorParams, VarianceThresholdSelectorParams

All Known Implementing Classes:

AFTSurvivalRegression, AFTSurvivalRegressionModel, BisectingKMeans, BisectingKMeansModel, ChiSqSelector, ChiSqSelectorModel, ClassificationModel, Classifier, ClusteringEvaluator, DecisionTreeClassificationModel, DecisionTreeClassifier, DecisionTreeRegressionModel, DecisionTreeRegressor, DistributedLDAModel, FMClassificationModel, FMClassifier, FMRegressionModel, FMRegressor, GaussianMixture, GaussianMixtureModel, GBTClassificationModel, GBTClassifier, GBTRegressionModel, GBTRegressor, GeneralizedLinearRegression, GeneralizedLinearRegressionModel, IsotonicRegression, IsotonicRegressionModel, KMeans, KMeansModel, LDA, LDAModel, LinearRegression, LinearRegressionModel, LinearSVC, LinearSVCModel, LocalLDAModel, LogisticRegression, LogisticRegressionModel, MultilayerPerceptronClassificationModel, MultilayerPerceptronClassifier, NaiveBayes, NaiveBayesModel, OneVsRest, OneVsRestModel, PredictionModel, Predictor, ProbabilisticClassificationModel, ProbabilisticClassifier, RandomForestClassificationModel, RandomForestClassifier, RandomForestRegressionModel, RandomForestRegressor, RegressionModel, Regressor, RFormula, RFormulaModel, UnivariateFeatureSelector, UnivariateFeatureSelectorModel, VarianceThresholdSelector, VarianceThresholdSelectorModel

public interface HasFeaturesCol
extends Params

Trait for shared param featuresCol (default: "features"). This trait may be changed or removed between minor versions.

Method Summary

Modifier and Type	Method and Description
Param<String>	featuresCol() Param for features column name.
String	getFeaturesCol()

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, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Methods inherited from interface org.apache.spark.ml.util.Identifiable

toString, uid

Method Detail

featuresCol

Param<String> featuresCol()

Param for features column name.

Returns:

(undocumented)

getFeaturesCol

String getFeaturesCol()