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LogisticRegressionAnalysis Properties |
The LogisticRegressionAnalysis type exposes the following members.
Properties| Name | Description | |
|---|---|---|
 | Array | Obsolete.
Gets the source matrix from which the analysis was run.
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| ChiSquare |
Gets the Chi-Square (Likelihood Ratio) Test for the model.
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| Coefficients |
Gets the collection of coefficients of the model.
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| CoefficientValues |
Gets the value of each coefficient.
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| ComputeInnerModels |
Gets or sets whether nested models should be computed in
order to calculate the likelihood-ratio test of each of
the coefficients. Default is false.
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| Confidences |
Gets the 95% Confidence Intervals (C.I.)
for each coefficient found in the regression.
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| Deviance |
Gets the Deviance of the model.
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| InformationMatrix |
Gets the information matrix obtained during learning.
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| Inputs |
Gets or sets the name of the input variables for the model.
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| Iterations |
Gets or sets the maximum number of iterations to be
performed by the regression algorithm. Default is 50.
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| LikelihoodRatioTests |
Gets the Likelihood-Ratio Tests for each coefficient.
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| LogLikelihood |
Gets the Log-Likelihood for the model.
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| NumberOfInputs |
Gets the number of inputs accepted by the model.
(Inherited from TransformBaseTInput, TOutput.) |
| NumberOfOutputs |
Gets the number of outputs generated by the model.
(Inherited from TransformBaseTInput, TOutput.) |
| NumberOfSamples |
Gets the number of samples used to compute the analysis.
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| OddsRatios |
Gets the Odds Ratio for each coefficient
found during the logistic regression.
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| Output |
Gets or sets the name of the output variable for the model.
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| Outputs | Obsolete.
Gets the dependent variable value
for each of the source input points.
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| Regression |
Gets the Logistic Regression model created
and evaluated by this analysis.
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| Regularization |
Gets or sets the regularization value to be
added in the objective function. Default is
1e-10.
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| Result | Obsolete.
Gets the resulting probabilities obtained
by the logistic regression model.
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| Source | Obsolete.
Gets the source matrix from which the analysis was run.
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| StandardErrors |
Gets the Standard Error for each coefficient
found during the logistic regression.
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| Token |
Gets or sets a cancellation token that can be used to
stop the learning algorithm while it is running.
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| Tolerance |
Gets or sets the difference between two iterations of the regression
algorithm when the algorithm should stop. The difference is calculated
based on the largest absolute parameter change of the regression. Default
is 1e-5.
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| WaldTests |
Gets the Wald Tests for each coefficient.
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| Weights | Obsolete.
Gets the sample weight associated with each input vector.
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See Also