LogisticRegressionModel Methods

Methods

Compute() Computes the model.
(Inherited from Model)
Obsolete.
Compute(ParallelOptions) Computes the model.
(Inherited from Model)
Obsolete.
Contains Returns whether another ClassificationModel<T> is nested within this instance.
(Inherited from ClassificationModel<T>)
EqualsDetermines whether the specified object is equal to the current object.
(Inherited from Object)
FinalizeAllows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object)
Fit() Fits the model to the data.
(Inherited from Model)
Fit(ParallelOptions) Fits the model to the data.
(Inherited from Model)
FitCore Fits the model to the data.
(Overrides Model.FitCore(ModelInput, ParallelOptions))
GetAkaikeInformationCriterion Returns the Akaike information criterion (AIC) value for the model.
GetBaseLogLikelihood Returns the log-likelihood of the model containing only a constant term.
GetBayesianInformationCriterion Returns the Bayesian information criterion (BIC) value for the model.
GetCoxAndSnellPseudoRSquared Returns the Cox & Snell pseudo R-squared value of the model.
GetHashCodeServes as the default hash function.
(Inherited from Object)
GetInformationMatrix Calculates the information matrix for the regression.
GetLikelihoodRatioTest() Returns a test to verify the significance of the logistic model.
GetLikelihoodRatioTest(LogisticRegressionModel) Returns a test to verify the significance of the logistic model.
GetMcFaddenPseudoRSquared Returns the McFadden pseudo R-squared value of the model.
GetNagelkerkePseudoRSquared Returns the Nagelkerke pseudo R-squared value of the model.
GetPearsonGoodnessOfFitTest Returns the Wald test for all the parameters in the regression.
GetTypeGets the Type of the current instance.
(Inherited from Object)
GetWaldTest() Returns the Wald test for all the parameters in the regression.
GetWaldTest(Int32[]) Returns the Wald test for the selected parameters in the regression.
MemberwiseCloneCreates a shallow copy of the current Object.
(Inherited from Object)
Predict(IDataFrame, ModelInputFormat) Predicts the most likely class based on the specified features.
(Inherited from ClassificationModel<T>)
Predict(Matrix<T>, ModelInputFormat) Predicts the value of the output corresponding to the specified features.
(Inherited from ClassificationModel<T>)
Predict(Vector<T>, ModelInputFormat) Predicts the value of the output corresponding to the specified input.
(Inherited from ClassificationModel<T>)
PredictCore(Matrix<Double>, Boolean) Predicts the value of the dependent variable based on the specified values of the features.
(Overrides ClassificationModel<T>.PredictCore(Matrix<T>, Boolean))
PredictCore(Vector<Double>, Boolean) Predicts the class based on the specified values of the features.
(Overrides ClassificationModel<T>.PredictCore(Vector<T>, Boolean))
PredictProbabilities(IDataFrame, ModelInputFormat) Predicts the value of the output corresponding to the specified input.
(Inherited from ClassificationModel<T>)
PredictProbabilities(Matrix<T>, ModelInputFormat) Predicts the value of the output corresponding to the specified features.
(Inherited from ClassificationModel<T>)
PredictProbabilities(Vector<T>, ModelInputFormat) Predicts the value of the output corresponding to the specified input.
(Inherited from ClassificationModel<T>)
PredictProbabilitiesCore(Matrix<Double>, Matrix<Double>, Boolean) Predicts the probabilities of each class based on the specified values of the features.
(Overrides ClassificationModel<T>.PredictProbabilitiesCore(Matrix<T>, Matrix<Double>, Boolean))
PredictProbabilitiesCore(Vector<Double>, Vector<Double>, Boolean) Predicts the probabilities of each class based on the specified values of the features.
(Overrides ClassificationModel<T>.PredictProbabilitiesCore(Vector<T>, Vector<Double>, Boolean))
PredictProbabilitiesInto(IDataFrame, Matrix<Double>, ModelInputFormat) Predicts the value of the output corresponding to the specified input.
(Inherited from ClassificationModel<T>)
PredictProbabilitiesInto(Matrix<T>, Matrix<Double>, ModelInputFormat) Predicts the value of the output corresponding to the specified features.
(Inherited from ClassificationModel<T>)
PredictProbabilitiesInto(Vector<T>, Vector<Double>, ModelInputFormat) Predicts the probabilities of each class based on the specified features.
(Inherited from ClassificationModel<T>)
ResetComputation Clears all fitted model parameters.
(Inherited from Model)
Obsolete.
ResetFit Clears all fitted model parameters.
(Inherited from Model)
SetDataSource Uses the specified data frame as the source for all input variables.
(Inherited from Model)
Summarize() Returns a string containing a human-readable summary of the object using default options.
(Inherited from Model)
Summarize(SummaryOptions) Returns a string containing a human-readable summary of the object using the specified options.
(Overrides Model.Summarize(SummaryOptions))
ToStringReturns a string that represents the current object.
(Inherited from Model)

See Also