org.apache.spark.mllib

classification

package classification

Visibility
  1. Public
  2. All

Type Members

  1. trait ClassificationModel extends Serializable

    :: Experimental :: Represents a classification model that predicts to which of a set of categories an example belongs.

  2. class LogisticRegressionModel extends GeneralizedLinearModel with ClassificationModel with Serializable with Saveable with PMMLExportable

    Classification model trained using Multinomial/Binary Logistic Regression.

  3. class LogisticRegressionWithLBFGS extends GeneralizedLinearAlgorithm[LogisticRegressionModel] with Serializable

    Train a classification model for Multinomial/Binary Logistic Regression using Limited-memory BFGS.

  4. class LogisticRegressionWithSGD extends GeneralizedLinearAlgorithm[LogisticRegressionModel] with Serializable

    Train a classification model for Binary Logistic Regression using Stochastic Gradient Descent.

  5. class NaiveBayes extends Serializable with Logging

    Trains a Naive Bayes model given an RDD of (label, features) pairs.

  6. class NaiveBayesModel extends ClassificationModel with Serializable with Saveable

    Model for Naive Bayes Classifiers.

  7. class SVMModel extends GeneralizedLinearModel with ClassificationModel with Serializable with Saveable with PMMLExportable

    Model for Support Vector Machines (SVMs).

  8. class SVMWithSGD extends GeneralizedLinearAlgorithm[SVMModel] with Serializable

    Train a Support Vector Machine (SVM) using Stochastic Gradient Descent.

  9. class StreamingLogisticRegressionWithSGD extends StreamingLinearAlgorithm[LogisticRegressionModel, LogisticRegressionWithSGD] with Serializable

    :: Experimental :: Train or predict a logistic regression model on streaming data.

Value Members

  1. object LogisticRegressionModel extends Loader[LogisticRegressionModel] with Serializable

    Annotations
    @Since( "1.3.0" )
  2. object LogisticRegressionWithSGD extends Serializable

    Top-level methods for calling Logistic Regression using Stochastic Gradient Descent.

  3. object NaiveBayes extends Serializable

    Top-level methods for calling naive Bayes.

  4. object NaiveBayesModel extends Loader[NaiveBayesModel] with Serializable

    Annotations
    @Since( "1.3.0" )
  5. object SVMModel extends Loader[SVMModel] with Serializable

    Annotations
    @Since( "1.3.0" )
  6. object SVMWithSGD extends Serializable

    Top-level methods for calling SVM.

Ungrouped