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 |
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>