| LogisticRegression Class |
Namespace: Emgu.CV.ML
The LogisticRegression type exposes the following members.
| Name | Description | |
|---|---|---|
| LogisticRegression |
Initializes a new instance of the LogisticRegression class.
|
| Name | Description | |
|---|---|---|
| AlgorithmPtr |
Return the pointer to the algorithm object
| |
| Iterations |
Number of iterations
| |
| LearningRate |
Learning rate
| |
| MiniBatchSize |
Specifies the number of training samples taken in each step of Mini-Batch Gradient Descent
| |
| Ptr |
Pointer to the unmanaged object
(Inherited from UnmanagedObject.) | |
| Regularization |
Kind of regularization to be applied
| |
| StatModelPtr |
Return the pointer to the StatModel object
| |
| TermCriteria |
Termination criteria of the algorithm
| |
| TrainMethod |
Kind of training method to be applied
|
| Name | Description | |
|---|---|---|
| Dispose |
The dispose function that implements IDisposable interface
(Inherited from DisposableObject.) | |
| DisposeObject |
Release the unmanaged resources
(Overrides DisposableObjectDisposeObject.) | |
| Equals | (Inherited from Object.) | |
| Finalize |
Destructor
(Inherited from DisposableObject.) | |
| GetHashCode | (Inherited from Object.) | |
| GetType | (Inherited from Object.) | |
| MemberwiseClone | (Inherited from Object.) | |
| ReleaseManagedResources |
Release the managed resources. This function will be called during the disposal of the current object.
override ride this function if you need to call the Dispose() function on any managed IDisposable object created by the current object
(Inherited from DisposableObject.) | |
| ToString | (Inherited from Object.) |
| Name | Description | |
|---|---|---|
| _ptr |
A pointer to the unmanaged object
(Inherited from UnmanagedObject.) |
| Name | Description | |
|---|---|---|
| Clear |
Clear the statistic model
(Defined by StatModelExtensions.) | |
| Predict |
Predicts response(s) for the provided sample(s)
(Defined by StatModelExtensions.) | |
| Read |
Reads algorithm parameters from a file storage.
(Defined by AlgorithmExtensions.) | |
| Save |
Save the statistic model to file
(Defined by StatModelExtensions.) | |
| Train(TrainData, Int32) | Overloaded.
Trains the statistical model.
(Defined by StatModelExtensions.) | |
| Train(IInputArray, DataLayoutType, IInputArray) | Overloaded.
Trains the statistical model.
(Defined by StatModelExtensions.) | |
| Write |
Stores algorithm parameters in a file storage
(Defined by AlgorithmExtensions.) |