Regularized
Methods
| Compute() |
Computes the model.
(Inherited from Model) |
| Compute( |
Computes the model.
(Inherited from Model) |
| Contains |
Returns whether another RegressionModel<T> is nested
within this instance.
(Inherited from RegressionModel<T>) |
| Deploy | Creates a deployed copy of this model containing only the state required for prediction. |
| Deploy |
Converts this instance into a deployed model by releasing any training
data and diagnostic information that is not required for prediction.
(Inherited from Model) |
| Deploy |
Releases model state that is not required for prediction.
(Overrides Model.DeployInPlaceCore()) |
| 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)) |
| From | Reconstructs a fitted RegularizedRegressionModel from a JSON string. |
| Get |
Returns the Akaike information criterion (AIC) value for the model.
(Inherited from RegressionModel<T>) |
| Get |
Returns the Bayesian information criterion (BIC) value for the model.
(Inherited from RegressionModel<T>) |
| Get | Gets the Durbin-Watson statistic for the residuals of the regression. |
| Get | Serves as the default hash function. (Inherited from Object) |
| Get | Returns a test to verify that the residuals follow a normal distribution. |
| Get | Returns a test to verify that the residuals follow a normal distribution. |
| Get | Returns a matrix whose rows contain the parameter values of the model using the corresponding value in the supplied vector of regularization parameters. |
| Get | Constructs a vector of suitable regularization parameter values based on the model's data. |
| Get | Constructs a range of suitable regularization parameter values based on the model's data. |
| Get | Constructs a range of suitable regularization parameter values based on the model's data. |
| 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 value of the output corresponding to
the specified features.
(Inherited from RegressionModel<T>) |
| Predict( |
Predicts the value of the output corresponding to
the specified features.
(Inherited from RegressionModel<T>) |
| Predict( |
Predicts the value of the output corresponding to
the specified features.
(Inherited from RegressionModel<T>) |
| Predict |
Predicts the value of the dependent variable based on
the specified values of the features.
(Inherited from RegressionModel<T>) |
| Predict |
Predicts the value of the dependent variable based on
the specified values of the features.
(Inherited from RegressionModel<T>) |
| Reset |
Clears all fitted model parameters.
(Inherited from Model) |
| 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 RegressionModel<T>) |
| ToJson | Serializes the fitted RegularizedRegressionModel to a JSON string. |
| ToString | Returns a string that represents the current object. (Inherited from Model) |