Classification Model<T> Class
Represents a statistical model used for classification.
Definition
Namespace: Numerics.NET.DataAnalysis.Models
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.2
C#
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.2
public abstract class ClassificationModel<T> : Model
- Derived
Type Parameters
- T
Remarks
This is an abstract base class and cannot be instantiated directly. Instead, use one of the inherited types, as listed in the table below:
Class | Description |
---|---|
Logistic | A binary or multinomial logistic regression model with one or more independent variables. |
Linear | A linear discriminant analysis model with multiple independent variables. |
Note to inheritors: When you inherit from ClassificationModel<T>, you must override FitCore(ModelInput, ParallelOptions).
Constructors
Classification | Constructs a new classification model based on a model specification. |
Properties
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. |
Category | Gets the category index of the dependent variable or targets. |
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. |
Fitted |
Gets whether the model has been computed.
(Inherited from Model) |
Independent | Gets a matrix whose columns contain the independent variables in the model. |
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. |
Predicted | Gets a vector containing the model's predicted values for the dependent variable. |
Predictions | Gets a vector containing the model's predicted values for the dependent variable. |
Probability | Gets a matrix containing the residuals of the model. |
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. |
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.
(Inherited from Model) |
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. |
Predict( | Predicts the value of the output corresponding to the specified features. |
Predict( | Predicts the value of the output corresponding to the specified input. |
Predict | Predicts the value of the dependent variable based on the specified values of the features. |
Predict | Predicts the class based on the specified values of the features. |
Predict | Predicts the value of the output corresponding to the specified input. |
Predict | Predicts the value of the output corresponding to the specified features. |
Predict | Predicts the value of the output corresponding to the specified input. |
Predict | Predicts the probabilities of each class based on the specified values of the features. |
Predict | Predicts the probabilities of each class based on the specified values of the features. |
Predict | Predicts the value of the output corresponding to the specified input. |
Predict | Predicts the value of the output corresponding to the specified features. |
Predict | Predicts the probabilities of each class based on the specified features. |
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.
(Inherited from Model) |
ToString | Returns a string that represents the current object. (Inherited from Model) |