org.apache.spark.ml.regression

Class GeneralizedLinearRegressionTrainingSummary

Object

org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary

org.apache.spark.ml.regression.GeneralizedLinearRegressionTrainingSummary

All Implemented Interfaces:

java.io.Serializable

public class GeneralizedLinearRegressionTrainingSummary
extends GeneralizedLinearRegressionSummary
implements scala.Serializable

:: Experimental :: 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 and Description
double[]	coefficientStandardErrors() Standard error of estimated coefficients and intercept.
int	numIterations()
double[]	pValues() Two-sided p-value of estimated coefficients and intercept.
String	solver()
double[]	tValues() T-statistic of estimated coefficients and intercept.

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 Object

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

Method Detail

numIterations

public int numIterations()

solver

public String solver()

coefficientStandardErrors

public double[] coefficientStandardErrors()

Standard error of estimated coefficients and intercept. This value is only available when the underlying WeightedLeastSquares using the "normal" solver.

If GeneralizedLinearRegression.fitIntercept is set to true, then the last element returned corresponds to the intercept.

Returns:

(undocumented)

tValues

public double[] tValues()

T-statistic of estimated coefficients and intercept. This value is only available when the underlying WeightedLeastSquares using the "normal" solver.

If GeneralizedLinearRegression.fitIntercept is set to true, then the last element returned corresponds to the intercept.

Returns:

(undocumented)

pValues

public double[] pValues()

Two-sided p-value of estimated coefficients and intercept. This value is only available when the underlying WeightedLeastSquares using the "normal" solver.

If GeneralizedLinearRegression.fitIntercept is set to true, then the last element returned corresponds to the intercept.

Returns:

(undocumented)