public class GeneralizedLinearRegressionTrainingSummary extends GeneralizedLinearRegressionSummary implements scala.Serializable
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
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.
|
aic, degreesOfFreedom, deviance, dispersion, nullDeviance, predictionCol, predictions, rank, residualDegreeOfFreedom, residualDegreeOfFreedomNull, residuals, residuals
public int numIterations()
public String solver()
public double[] coefficientStandardErrors()
If GeneralizedLinearRegression.fitIntercept
is set to true,
then the last element returned corresponds to the intercept.
public double[] tValues()
If GeneralizedLinearRegression.fitIntercept
is set to true,
then the last element returned corresponds to the intercept.
public double[] pValues()
If GeneralizedLinearRegression.fitIntercept
is set to true,
then the last element returned corresponds to the intercept.