Classification
Definition
Namespace: Extreme.DataAnalysis.Models
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23
Overload List
| 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. |
ClassificationModel<T>.PredictCore(Matrix<T>, Boolean)
Predicts the value of the dependent variable based on
the specified values of the features.
protected virtual CategoricalVector<int> PredictCore(
Matrix<T> features,
bool modelFeaturesOnly
)Parameters
- features Matrix<T>
- A matrix containing the values for the independent variables.
- modelFeaturesOnly Boolean
- Specifies whether features includes only features that appear in the fitted model.
Return Value
CategoricalVector<Int32>A vector containing the class with the highest probability for as predicted by the model for each row in features.
Exceptions
| Argument | features is null. |
| Dimension | The number of columns of features does not match the required number of values. |
ClassificationModel<T>.PredictCore(Vector<T>, Boolean)
Predicts the class based on
the specified values of the features.
protected virtual int PredictCore(
Vector<T> features,
bool modelFeaturesOnly
)Parameters
- features Vector<T>
- A vector containing the values for the independent variables.
- modelFeaturesOnly Boolean
- Specifies whether features includes only features that appear in the fitted model.
Return Value
Int32The class with the highest probability for the specified features as predicted by the model.
Exceptions
| Argument | features is null. |
| Dimension | The length of features does not match the required number of values. |