Represents a statistical model used for classification.
Extreme.Numerics.Net40 (in Extreme.Numerics.Net40.dll) Version: 6.0.16073.0 (6.0.17114.0)
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| Name | Description |
|---|
 | BaseFeatureIndex |
Gets an index containing the keys of the columns
that are required inputs to the model.
(Inherited from Model.) |
| CanPredictProbabilities |
Gets whether the classifier supports predicting probabilities
for each class.
|
| CategoryIndex |
Gets the category index of the dependent variable or targets.
|
| Computed |
Gets whether the regression model has been computed.
(Inherited from Model.) |
| Data |
Gets an object that contains all the data used as input to the model.
(Inherited from Model.) |
| DependentVariable |
Gets a vector that contains the dependent variable that is to be fitted.
|
| IndependentVariables |
Gets a matrix whose columns contain the independent variables in the model.
|
| InputSchema |
Gets the schema for the features used for fitting the model.
(Inherited from Model.) |
| LogLikelihood |
Gets the log-likelihood of the fitted model.
|
| MaxDegreeOfParallelism |
Gets or sets the maximum degree of parallelism enabled by this instance.
(Inherited from Model.) |
| ModelSchema |
Gets the collection of variables used in the model.
(Inherited from Model.) |
 | ModelSubset |
Returns an array of indexes of final model features in the
set of input features.
(Inherited from Model.) |
| NumberOfObservations |
Gets the number of observations the model is based on.
(Inherited from Model.) |
| ParallelOptions |
Gets or sets an object that specifies how the calculation of the model should be parallelized.
(Inherited from Model.) |
| ParameterValues |
Gets the collection of parameters associated with this model.
|
| PredictedLogProbabilities |
Gets a vector containing the model's predicted values for the dependent variable.
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| PredictedProbabilities |
Gets a vector containing the model's predicted values for the dependent variable.
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| Predictions |
Gets a vector containing the model's predicted values for the dependent variable.
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| ProbabilityResiduals |
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.) |
| SupportsWeights |
Indicates whether the model supports case weights.
(Inherited from Model.) |
| Weights |
Gets or sets the actual weights.
(Inherited from Model.) |
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| Name | Description |
|---|
 | Compute |
Computes the model.
(Inherited from Model.) |
| Compute(ParallelOptions) |
Computes the model.
(Inherited from Model.) |
 | ComputeModel |
Computes the model.
(Inherited from Model.) |
| ComputeModel(ParallelOptions) |
Fits the model to the data.
(Inherited from Model.) |
| ComputeModel(ModelInput, ParallelOptions) |
Computes the model using the specified parallelization options.
(Inherited from Model.) |
| Contains |
Returns whether another ClassificationModel is nested
within this instance.
|
| Equals | Determines whether the specified Object is equal to the current 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(ParallelOptions) |
Fits the model to the data.
(Inherited from Model.) |
| FitCore |
Computes the model to the specified input
using the specified parallelization options.
(Inherited from Model.) |
| GetHashCode | Serves as a hash function for a particular type. (Inherited from Object.) |
| GetType | Gets the Type of the current instance. |
| MemberwiseClone | Creates a shallow copy of the current Object. |
| Predict(IDataFrame, ModelInputFormat) |
Predicts the most likely class based on
the specified features.
|
| Predict(MatrixDouble, ModelInputFormat) |
Predicts the value of the output corresponding to
the specified features.
|
| Predict(VectorDouble, ModelInputFormat) |
Predicts the value of the output corresponding to
the specified input.
|
| PredictCore(MatrixDouble, Boolean, Boolean) |
Predicts the value of the dependent variable based on
the specified values of the features.
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| PredictCore(VectorDouble, Boolean, Boolean) |
Predicts the class based on
the specified values of the features.
|
| PredictProbabilities(IDataFrame, ModelInputFormat) |
Predicts the value of the output corresponding to
the specified input.
|
| PredictProbabilities(MatrixDouble, ModelInputFormat) |
Predicts the value of the output corresponding to
the specified features.
|
| PredictProbabilities(VectorDouble, ModelInputFormat) |
Predicts the value of the output corresponding to
the specified input.
|
| PredictProbabilitiesCore(MatrixDouble, MatrixDouble, Boolean, Boolean) |
Predicts the probabilities of each class based on
the specified values of the features.
|
| PredictProbabilitiesCore(VectorDouble, VectorDouble, Boolean, Boolean) |
Predicts the probabilities of each class based on
the specified values of the features.
|
| PredictProbabilitiesInto(IDataFrame, MatrixDouble, ModelInputFormat) |
Predicts the value of the output corresponding to
the specified input.
|
| PredictProbabilitiesInto(MatrixDouble, MatrixDouble, ModelInputFormat) |
Predicts the value of the output corresponding to
the specified features.
|
| PredictProbabilitiesInto(VectorDouble, VectorDouble, ModelInputFormat) |
Predicts the probabilities of each class based on
the specified features.
|
| ResetComputation |
Clears all computed model parameters.
(Inherited from Model.) |
| SetDataSource |
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(SummaryOptions) |
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.) |
This is an abstract base class and cannot be instantiated directly. Instead, use one of the
inherited types, as listed in the table below: