LinearDiscriminantAnalysis Properties

Properties

AssumeEqualPriors Gets or sets whether the group priors are assumed to be equal.
BaseFeatureIndex Gets an index containing the keys of the columns that are required inputs to the model.
(Inherited from Model)
CanonicalStructureMatrix Gets the canonical structure matrix of the discriminant analysis.
CanPredictProbabilities Gets whether the classifier supports predicting probabilities for each class.
(Overrides ClassificationModel<T>.CanPredictProbabilities)
CategoryIndex Gets the category index of the dependent variable or targets.
(Inherited from ClassificationModel<T>)
Computed Gets whether the model has been computed.
(Inherited from Model)
Obsolete.
Data Gets an object that contains all the data used as input to the model.
(Inherited from Model)
DependentVariable Gets a vector that contains the dependent variable that is to be fitted.
(Inherited from ClassificationModel<T>)
DiscriminantDirections Gets the collection of discriminant functions.
DiscriminantFunctions Gets the collection of discriminant functions.
Fitted Gets whether the model has been computed.
(Inherited from Model)
IndependentVariables Gets a matrix whose columns contain the independent variables in the model.
(Inherited from ClassificationModel<T>)
InputSchema Gets the schema for the features used for fitting the model.
(Inherited from Model)
MaxDegreeOfParallelism Gets or sets the maximum degree of parallelism enabled by this instance.
(Inherited from Model)
ModelSchema Gets the collection of variables used in the model.
(Inherited from Model)
NumberOfObservations Gets the number of observations the model is based on.
(Inherited from Model)
ParallelOptions Gets or sets an object that specifies how the calculation of the model should be parallelized.
(Inherited from Model)
PredictedLogProbabilities Gets a vector containing the model's predicted values for the dependent variable.
(Inherited from ClassificationModel<T>)
PredictedProbabilities Gets a vector containing the model's predicted values for the dependent variable.
(Inherited from ClassificationModel<T>)
Predictions Gets a vector containing the model's predicted values for the dependent variable.
(Inherited from ClassificationModel<T>)
Priors Gets or sets the prior probabilities of the groups.
ProbabilityResiduals Gets a matrix containing the residuals of the model.
(Inherited from ClassificationModel<T>)
Status Gets the status of the model, which determines which information is available.
(Inherited from Model)
SupportsWeights Indicates whether the model supports case weights.
(Inherited from Model)
Weights Gets or sets the actual weights.
(Inherited from Model)

See Also