Class: GeneralizedLinearRegressionTrainingSummary

eclairjs/ml/regression.GeneralizedLinearRegressionTrainingSummary

:: Experimental :: Summary of GeneralizedLinearRegression fitting and model.

Constructor

new GeneralizedLinearRegressionTrainingSummary(dataset, origModel, diagInvAtWA, numIterations, solver)

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

Extends

Methods

coefficientStandardErrors() → {Promise.<Array.<number>>}

Standard error of estimated coefficients and intercept.
Overrides:
Source:
Returns:
Type
Promise.<Array.<number>>

pValues() → {Promise.<Array.<number>>}

Two-sided p-value of estimated coefficients and intercept.
Overrides:
Source:
Returns:
Type
Promise.<Array.<number>>

tValues() → {Promise.<Array.<number>>}

T-statistic of estimated coefficients and intercept.
Overrides:
Source:
Returns:
Type
Promise.<Array.<number>>

uid() → {Promise.<string>}

An immutable unique ID for the object and its derivatives.
Overrides:
Source:
Returns:
Type
Promise.<string>