Package org.apache.spark.ml.regression

Class GeneralizedLinearRegressionTrainingSummary

Object

org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary

org.apache.spark.ml.regression.GeneralizedLinearRegressionTrainingSummary

All Implemented Interfaces:

Serializable, scala.Serializable

public class GeneralizedLinearRegressionTrainingSummary
extends GeneralizedLinearRegressionSummary
implements scala.Serializable

Summary of GeneralizedLinearRegression fitting and model.

param: dataset Dataset to be summarized. param: origModel Model to be summarized. This is copied to create an internal model which cannot be modified from outside. param: diagInvAtWA diagonal of matrix (A^T * W * A)^-1 in the last iteration param: numIterations number of iterations param: solver the solver algorithm used for model training

See Also:

• Serialized Form

Method Summary

Modifier and Type	Method	Description
double[]	coefficientStandardErrors()
int	numIterations()
double[]	pValues()
String	solver()
String	toString()
double[]	tValues()

Methods inherited from class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary

aic, degreesOfFreedom, deviance, dispersion, nullDeviance, numInstances, predictionCol, predictions, rank, residualDegreeOfFreedom, residualDegreeOfFreedomNull, residuals, residuals

Methods inherited from class java.lang.Object

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

Method Details

coefficientStandardErrors

public double[] coefficientStandardErrors()

numIterations

public int numIterations()

pValues

public double[] pValues()

solver

public String solver()

tValues

public double[] tValues()

toString

public String toString()

Overrides:

toString in class Object