C++ API Reference for Intel® Data Analytics Acceleration Library 2020 Update 1
Parameter for the EM for GMM algorithm More...
Parameter | ( | const size_t | nComponents, |
const services::SharedPtr< covariance::BatchImpl > & | covariance, | ||
const size_t | maxIterations = 10 , |
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const double | accuracyThreshold = 1.0e-04 , |
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const double | regularizationFactor = 0.01 , |
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const CovarianceStorageId | covarianceStorage = full |
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) |
Constructs the parameter of EM for GMM algorithm
[in] | nComponents | Number of components in the Gaussian mixture model |
[in] | covariance | Pointer to the algorithm that computes the covariance |
[in] | maxIterations | Maximal number of iterations of the algorithm |
[in] | accuracyThreshold | Threshold for the termination of the algorithm |
[in] | regularizationFactor | Factor for covariance regularization in case of ill-conditional data |
[in] | covarianceStorage | Type of covariance in the Gaussian mixture model. |
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virtual |
Checks the correctness of the parameter
double accuracyThreshold |
Threshold for the termination of the algorithm.
services::SharedPtr<covariance::BatchImpl> covariance |
Pointer to the algorithm that computes the covariance
CovarianceStorageId covarianceStorage |
Type of covariance in the Gaussian mixture model.
size_t maxIterations |
Maximal number of iterations of the algorithm.
size_t nComponents |
Number of components in the Gaussian mixture model
double regularizationFactor |
Factor for covariance regularization in case of ill-conditional data
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