org.apache.spark.mllib.util

Class LogisticRegressionDataGenerator

Object

org.apache.spark.mllib.util.LogisticRegressionDataGenerator

public class LogisticRegressionDataGenerator
extends Object

Generate test data for LogisticRegression. This class chooses positive labels with probability probOne and scales features for positive examples by eps.

Constructor Summary

Constructors

Constructor and Description
LogisticRegressionDataGenerator()

Method Summary

Modifier and Type	Method and Description
static RDD<LabeledPoint>	generateLogisticRDD(SparkContext sc, int nexamples, int nfeatures, double eps, int nparts, double probOne) Generate an RDD containing test data for LogisticRegression.
static void	main(String[] args)

Methods inherited from class Object

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

Constructor Detail

LogisticRegressionDataGenerator

public LogisticRegressionDataGenerator()

Method Detail

generateLogisticRDD

public static RDD<LabeledPoint> generateLogisticRDD(SparkContext sc,
                                                    int nexamples,
                                                    int nfeatures,
                                                    double eps,
                                                    int nparts,
                                                    double probOne)

Generate an RDD containing test data for LogisticRegression.

Parameters:

sc - SparkContext to use for creating the RDD.

nexamples - Number of examples that will be contained in the RDD.

nfeatures - Number of features to generate for each example.

eps - Epsilon factor by which positive examples are scaled.

nparts - Number of partitions of the generated RDD. Default value is 2.

probOne - Probability that a label is 1 (and not 0). Default value is 0.5.

Returns:

(undocumented)

main

public static void main(String[] args)