Linear Discriminant Analysis Class
Represents a linear discriminant classification model.
Definition
Namespace: Numerics.NET.Statistics.Multivariate
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.3
C#
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.3
public class LinearDiscriminantAnalysis : ClassificationModel<double>,
ITransformationModel
- Inheritance
- Object → Model → ClassificationModel<Double> → LinearDiscriminantAnalysis
- Implements
- ITransformationModel
Remarks
Use the LinearDiscriminantAnalysis class to represent a classification model that uses linear discriminant analysis. LinearDiscriminantAnalysis can also be used for dimensionality reduction. In this case, the features are projected onto the directions that most separate the groups.
Constructors
Linear | Constructs a new LinearDiscriminantAnalysis. |
Linear | Constructs a new LinearDiscriminantAnalysis. |
Linear | Constructs a fitted linear discriminant analysis model. |
Linear | Constructs a new LinearDiscriminantAnalysis. |
Linear | Constructs a new LinearDiscriminantAnalysis. |
Linear | Constructs a new SimpleRegressionModel. |
Properties
Base |
Gets an index containing the keys of the columns
that are required inputs to the model.
(Inherited from Model) |
Canonical | Gets the canonical structure matrix of the discriminant analysis. |
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 collection of discriminant functions. |
Fitted |
Gets whether the model has been computed.
(Inherited from Model) |
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) |
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) |
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) |
Inverse | Applies the inverse transformation to a set of observations. |
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) |
Transform | Applies the transformation to a set of observations. |
Extension Methods
Transform |
Applies the transformation to a set of observations.
(Defined by ModelExtensions) |
Transform |
Applies the transformation to a set of observations.
(Defined by ModelExtensions) |