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
aic() → {double}
Akaike Information Criterion (AIC) for the fitted model.
- Inherited From:
- Source:
Returns:
- Type
- double
coefficientStandardErrors() → {Array.<float>}
Standard error of estimated coefficients and intercept.
Returns:
- Type
- Array.<float>
degreesOfFreedom() → {double}
Degrees of freedom.
- Inherited From:
- Source:
Returns:
- Type
- double
deviance() → {double}
The deviance for the fitted model.
- Inherited From:
- Source:
Returns:
- Type
- double
dispersion() → {double}
The dispersion of the fitted model.
- Inherited From:
- Source:
Returns:
- Type
- double
nullDeviance() → {double}
The deviance for the null model.
- Inherited From:
- Source:
Returns:
- Type
- double
predictions() → {module:eclairjs/sql.Dataset}
Predictions output by the model's `transform` method.
- Inherited From:
- Source:
Returns:
pValues() → {Array.<double>}
Two-sided p-value of estimated coefficients and intercept.
Returns:
- Type
- Array.<double>
residualDegreeOfFreedom() → {int}
The residual degrees of freedom.
- Inherited From:
- Source:
Returns:
- Type
- int
residualDegreeOfFreedomNull() → {int}
The residual degrees of freedom for the null model.
- Inherited From:
- Source:
Returns:
- Type
- int
residuals(residualsTypeopt) → {module:eclairjs/sql.Dataset}
Get the residuals of the fitted model by type.
Parameters:
Name | Type | Attributes | Description |
---|---|---|---|
residualsType |
string |
<optional> |
The type of residuals which should be returned. Supported options: deviance, pearson, working and response. |
- Inherited From:
- Source:
Returns:
tValues() → {Array.<double>}
T-statistic of estimated coefficients and intercept.
Returns:
- Type
- Array.<double>