Linear Regression Model Properties
Properties
| Adjusted |
Gets the adjusted R Squared value for the regression.
(Inherited from RegressionModel<T>) |
| Anova |
Gets the AnovaTable that summarizes the results of this model.
(Inherited from RegressionModel<T>) |
| Base |
Gets an index containing the keys of the columns
that are required inputs to the model.
(Inherited from Model) |
| Coefficient | Gets the coefficient of variation for the regression. |
| Computed |
Gets whether the model has been computed.
(Inherited from Model) Obsolete. |
| Covariance |
Gets the covariance matrix of the model parameters.
(Inherited from RegressionModel<T>) |
| Data |
Gets an object that contains all the data used as input to the model.
(Inherited from Model) |
| Degrees |
Gets the total degrees of freedom of the data.
(Inherited from RegressionModel<T>) |
| Dependent |
Gets a vector that contains the dependent variable that is to be fitted.
(Inherited from RegressionModel<T>) |
| Fitted |
Gets whether the model has been computed.
(Inherited from Model) |
| FStatistic |
Gets the F statistic for the regression.
(Inherited from RegressionModel<T>) |
| Independent |
Gets a matrix whose columns contain the independent variables in the model.
(Inherited from RegressionModel<T>) |
| Input |
Gets the schema for the features used for fitting the model.
(Inherited from Model) |
| Leverage | Returns the leverage of each observation. |
| Log |
Gets the log-likelihood that the model generated the data.
(Inherited from RegressionModel<T>) |
| 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) |
| NoIntercept | Gets or sets whether to include the intercept or constant term in the regression 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) |
| Parameters |
Gets the collection of parameters associated with this model.
(Inherited from RegressionModel<T>) |
| Parameter |
Gets the values of the parameters associated with this model.
(Inherited from RegressionModel<T>) |
| Predicted | Gets the predicted R Squared value of the model. |
| Predictions |
Gets a vector containing the model's predicted values for the dependent variable.
(Inherited from RegressionModel<T>) |
| Press | Gets the predicted residual error sum of squares (PRESS) of the model. |
| PValue |
Gets the probability corresponding to the F statistic for the regression.
(Inherited from RegressionModel<T>) |
| Residuals |
Gets a vector containing the residuals of the model.
(Inherited from RegressionModel<T>) |
| Residual |
Gets the sum of squares of the residuals of the model.
(Inherited from RegressionModel<T>) |
| Ridge | Gets or sets the coefficient of the squared norm of the regression parameters for ridge regression. |
| RSquared |
Gets the R Squared value for the regression.
(Inherited from RegressionModel<T>) |
| Standard |
Gets the standard error of the regression.
(Inherited from RegressionModel<T>) |
| Status |
Gets the status of the model, which determines which information is available.
(Inherited from Model) |
| Steps | Gets the collection of steps performed in a stepwise regression. |
| Stepwise | Gets or sets an object that specifies options for performing stepwise regression. |
| Supports |
Indicates whether the model supports case weights.
(Overrides Model.SupportsWeights) |
| Variance | Returns the Variance Inflation Factor (VIF) for each variable in the model. |
| Weights |
Gets or sets the actual weights.
(Inherited from Model) |