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itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample > Class Template Reference
This class generates the parameter estimates for a mixture model using expectation maximization strategy.
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#include <itkExpectationMaximizationMixtureModelEstimator.h>
Inheritance diagram for itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >:
[legend]Collaboration diagram for itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >:
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Detailed Description
template<class TSample>
class itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >
This class generates the parameter estimates for a mixture model using expectation maximization strategy.
The first template argument is the type of the target sample data. This estimator expects one or more mixture model component objects of the classes derived from the MixtureModelComponentBase. The actual component (or module) parameters are updated by each component. Users can think this class as a strategy or a integration point for the EM procedure. The initial proportion (SetInitialProportions), the input sample (SetSample), the mixture model components (AddComponent), and the maximum iteration (SetMaximumIteration) are required. The EM procedure terminates when the current iteration reaches the maximum iteration or the model parameters converge.
Recent API changes: The static const macro to get the length of a measurement vector, MeasurementVectorSize has been removed to allow the length of a measurement vector to be specified at run time. It is now obtained at run time from the sample set as input. Please use the function GetMeasurementVectorSize() to get the length.
- See also:
- MixtureModelComponentBase, GaussianMixtureModelComponent
Definition at line 53 of file itkExpectationMaximizationMixtureModelEstimator.h.
Member Typedef Documentation
Member Enumeration Documentation
Constructor & Destructor Documentation
Member Function Documentation
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Adds a new component (or class). |
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Starts the estimation process |
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Gets the membership function specified by componentIndex argument. |
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Set/Gets the initial proportion values. The size of proportion vector should be same as the number of component (or classes) |
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Set/Gets the maximum number of iterations. When the optimization process reaches the maximum number of interations, even if the class parameters aren't converged, the optimization process stops. |
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Gets the total number of classes currently plugged in. |
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Gets the result proportion values |
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Gets the termination status |
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Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.
Reimplemented from itk::Object. |
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Set/Gets the initial proportion values. The size of proportion vector should be same as the number of component (or classes) |
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Set/Gets the maximum number of iterations. When the optimization process reaches the maximum number of interations, even if the class parameters aren't converged, the optimization process stops. |
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Sets the target data that will be classified by this |
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Runs the optimization process. |
The documentation for this class was generated from the following file:
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