Quadratic Discriminant Analysis Class
Represents a quadratic discriminant classification model.
Definition
Namespace: Numerics.NET.Statistics.Multivariate
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.7
C#
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.7
public class QuadraticDiscriminantAnalysis : ClassificationModel<double>
- Inheritance
- Object → Model → ClassificationModel<Double> → QuadraticDiscriminantAnalysis
Remarks
Use the QuadraticDiscriminantAnalysis class to represent a classification model that uses quadratic discriminant analysis. Unlike linear discriminant analysis, QDA does not assume that the covariance matrices of each class are identical. This makes it more flexible but requires more parameters to be estimated.
Constructors
Quadratic | Constructs a new empty QuadraticDiscriminantAnalysis. |
Quadratic | Constructs a new QuadraticDiscriminantAnalysis. |
Quadratic | Constructs a new QuadraticDiscriminantAnalysis. |
Properties
Assume | Gets or sets whether the group priors are assumed to be equal. |
Base |
Gets an index containing the keys of the columns
that are required inputs to the model.
(Inherited from Model) |
Can |
Gets whether the classifier supports predicting probabilities
for each class.
(Overrides ClassificationModel<T>.CanPredictProbabilities) |
Category |
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) |
Dependent |
Gets a vector that contains the dependent variable that is to be fitted.
(Inherited from ClassificationModel<T>) |
Discriminant | Gets the discriminant functions. |
Error | Gets the error rates. |
Fitted |
Gets whether the model has been computed.
(Inherited from Model) |
Group | Gets the group covariances. |
Group | Gets the group error rates. |
Group | Gets the group means. |
Group | Gets the group separability. |
Independent |
Gets a matrix whose columns contain the independent variables in the model.
(Inherited from ClassificationModel<T>) |
Input |
Gets the schema for the features used for fitting the model.
(Inherited from Model) |
Mahalanobis | Gets the Mahalanobis distances. |
Max |
Gets or sets the maximum degree of parallelism enabled by this instance.
(Inherited from Model) |
Model |
Gets the collection of variables used in the model.
(Inherited from Model) |
Number |
Gets the number of observations the model is based on.
(Inherited from Model) |
Parallel |
Gets or sets an object that specifies how the calculation of the model should be parallelized.
(Inherited from Model) |
Predicted |
Gets a vector containing the model's predicted values for the dependent variable.
(Inherited from ClassificationModel<T>) |
Predicted |
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. |
Probability |
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) |
Supports |
Indicates whether the model supports case weights.
(Inherited from Model) |
Total | Gets the total separability. |
Weights |
Gets or sets the actual weights.
(Inherited from Model) |
Methods
Compute() |
Computes the model.
(Inherited from Model) Obsolete. |
Compute( |
Computes the model.
(Inherited from Model) Obsolete. |
Contains |
Returns whether another ClassificationModel<T> is nested
within this instance.
(Inherited from ClassificationModel<T>) |
Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) |
Finalize | Allows 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( |
Fits the model to the data.
(Inherited from Model) |
Fit |
Computes the model to the specified input
using the specified parallelization options.
(Overrides Model.FitCore(ModelInput, ParallelOptions)) |
Get | Serves as the default hash function. (Inherited from Object) |
Get | Gets the Type of the current instance. (Inherited from Object) |
Memberwise | Creates a shallow copy of the current Object. (Inherited from Object) |
Predict( |
Predicts the most likely class based on
the specified features.
(Inherited from ClassificationModel<T>) |
Predict( |
Predicts the value of the output corresponding to
the specified features.
(Inherited from ClassificationModel<T>) |
Predict( |
Predicts the value of the output corresponding to
the specified input.
(Inherited from ClassificationModel<T>) |
Predict |
Predicts the value of the dependent variable based on
the specified values of the features.
(Inherited from ClassificationModel<T>) |
Predict |
Predicts the class based on
the specified values of the features.
(Inherited from ClassificationModel<T>) |
Predict |
Predicts the value of the output corresponding to
the specified input.
(Inherited from ClassificationModel<T>) |
Predict |
Predicts the value of the output corresponding to
the specified features.
(Inherited from ClassificationModel<T>) |
Predict |
Predicts the value of the output corresponding to
the specified input.
(Inherited from ClassificationModel<T>) |
Predict |
Predicts the probabilities of each class based on
the specified values of the features.
(Inherited from ClassificationModel<T>) |
Predict |
Predicts the probabilities of each class based on
the specified values of the features.
(Overrides ClassificationModel<T>.PredictProbabilitiesCore(Vector<T>, Vector<Double>, Boolean)) |
Predict |
Predicts the value of the output corresponding to
the specified input.
(Inherited from ClassificationModel<T>) |
Predict |
Predicts the value of the output corresponding to
the specified features.
(Inherited from ClassificationModel<T>) |
Predict |
Predicts the probabilities of each class based on
the specified features.
(Inherited from ClassificationModel<T>) |
Reset |
Clears all fitted model parameters.
(Inherited from Model) Obsolete. |
Reset |
Clears all fitted model parameters.
(Inherited from Model) |
Set |
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( |
Returns a string containing a human-readable summary of the object using the specified options.
(Overrides Model.Summarize(SummaryOptions)) |
ToString | Returns a string that represents the current object. (Inherited from Model) |