Expectation Maximization model
| All Members | Constructors | Methods | Properties | Fields | |
| Icon | Member | Description |
|---|---|---|
| EM()()() |
Create an Expectation Maximization model
| |
| EM(Matrix<(Of <(Single>)>), Matrix<(Of <(Single>)>), EMParams, Matrix<(Of <(Int32>)>)) |
Creaet an Expectation Maximization model using the specific training parameters
| |
| _ptr |
A pointer to the unmanaged object
(Inherited from UnmanagedObject.) | |
| Clear()()() |
Clear the statistic model
(Inherited from StatModel.) | |
| Dispose()()() |
The dispose function that implements IDisposable interface
(Inherited from DisposableObject.) | |
| Dispose(Boolean) |
Release the all the memory associate with this object
(Inherited from DisposableObject.) | |
| DisposeObject()()() |
Release the memory associated with this EM model
(Overrides DisposableObject.DisposeObject()()().) | |
| Equals(Object) | (Inherited from Object.) | |
| Finalize()()() |
Destructor
(Inherited from DisposableObject.) | |
| GetCovariances()()() |
Get the covariance matrices for each cluster
| |
| GetHashCode()()() | Serves as a hash function for a particular type. (Inherited from Object.) | |
| GetMeans()()() |
Get the mean of the clusters
| |
| GetProbabilities()()() |
Get the probability matrix
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| GetType()()() | Gets the Type of the current instance. (Inherited from Object.) | |
| GetWeights()()() |
Get the weights of the clusters
| |
| Load(String) |
Load the statistic model from file
(Inherited from StatModel.) | |
| MemberwiseClone()()() | Creates a shallow copy of the current Object. (Inherited from Object.) | |
| NumberOfClusters |
Get the number of clusters of this EM model
| |
| Predict(Matrix<(Of <(Single>)>), Matrix<(Of <(Single>)>)) |
Predit the probability of the samples | |
| Ptr |
Pointer to the unmanaged object
(Inherited from UnmanagedObject.) | |
| Save(String) |
Save the statistic model to file
(Inherited from StatModel.) | |
| ToString()()() | (Inherited from Object.) | |
| Train(Matrix<(Of <(Single>)>), Matrix<(Of <(Single>)>), EMParams, Matrix<(Of <(Int32>)>)) |
Train the EM model using the specific training data
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