org.apache.spark.mllib.regression.impl

Class GLMRegressionModel.SaveLoadV1_0$

Object

org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$

Enclosing class:

GLMRegressionModel

public static class GLMRegressionModel.SaveLoadV1_0$
extends Object

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	GLMRegressionModel.SaveLoadV1_0$.Data Model data for model import/export

Field Summary

Fields

Modifier and Type	Field and Description
static GLMRegressionModel.SaveLoadV1_0$	MODULE$ Static reference to the singleton instance of this Scala object.

Constructor Summary

Constructors

Constructor and Description
GLMRegressionModel.SaveLoadV1_0$()

Method Summary

Methods

Modifier and Type	Method and Description
org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0.Data	loadData(SparkContext sc, String path, String modelClass, int numFeatures) Helper method for loading GLM regression model data.
void	save(SparkContext sc, String path, String modelClass, Vector weights, double intercept) Helper method for saving GLM regression model metadata and data.
String	thisFormatVersion()

Methods inherited from class Object

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

Field Detail

MODULE$

public static final GLMRegressionModel.SaveLoadV1_0$ MODULE$

Static reference to the singleton instance of this Scala object.

Constructor Detail

GLMRegressionModel.SaveLoadV1_0$

public GLMRegressionModel.SaveLoadV1_0$()

Method Detail

thisFormatVersion

public String thisFormatVersion()

save

public void save(SparkContext sc,
        String path,
        String modelClass,
        Vector weights,
        double intercept)

Helper method for saving GLM regression model metadata and data.

Parameters:

modelClass - String name for model class, to be saved with metadata

loadData

public org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0.Data loadData(SparkContext sc,
                                                                                   String path,
                                                                                   String modelClass,
                                                                                   int numFeatures)

Helper method for loading GLM regression model data.

Parameters:

modelClass - String name for model class (used for error messages)

numFeatures - Number of features, to be checked against loaded data. The length of the weights vector should equal numFeatures.