Package org.apache.spark.mllib.classification

Class LogisticRegressionWithSGD

Object
org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm<LogisticRegressionModel>
org.apache.spark.mllib.classification.LogisticRegressionWithSGD
All Implemented Interfaces:
Serializable, org.apache.spark.internal.Logging
public class LogisticRegressionWithSGD extends GeneralizedLinearAlgorithm<LogisticRegressionModel> implements Serializable
Train a classification model for Binary Logistic Regression using Stochastic Gradient Descent. By default L2 regularization is used, which can be changed via LogisticRegressionWithSGD.optimizer.

Using LogisticRegressionWithLBFGS is recommended over this.

See Also:
Note:
Labels used in Logistic Regression should be {0, 1, ..., k - 1} for k classes multi-label classification problem.

  • Nested Class Summary

    Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

    org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter

  • Method Summary

    Modifier and Type
    Method
    Description
    GradientDescent
    optimizer()
    The optimizer to solve the problem.

    Methods inherited from class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm

    getNumFeatures, isAddIntercept, run, run, setIntercept, setValidateData

    Methods inherited from class java.lang.Object

    equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    Methods inherited from interface org.apache.spark.internal.Logging

    initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext