C++ API Reference for Intel® Data Analytics Acceleration Library 2019 Update 5
Parameter for the computation of initial values for the EM for GMM algorithm More...
| Parameter | ( | size_t | nComponents, |
| size_t | nTrials = 20, |
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| size_t | nIterations = 10, |
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| size_t | seed = 777, |
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| double | accuracyThreshold = 1.0e-04, |
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| em_gmm::CovarianceStorageId | covarianceStorage = em_gmm::full |
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| ) |
Constructs parameters of the EM for GMM algorithm
| [in] | nComponents | Number of components in the Gaussian mixture model |
| [in] | nTrials | Number of trials of short EM runs |
| [in] | nIterations | Number of iterations in every short EM run |
| [in] | seed | Seed for randomly generating data points to start the initialization of short EM |
| [in] | accuracyThreshold | Threshold for the termination of the algorithm |
| [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
| em_gmm::CovarianceStorageId covarianceStorage |
Type of covariance in the Gaussian mixture model.
| engines::EnginePtr engine |
Engine to be used for randomly generating data points to start the initialization of short EM
| size_t nComponents |
Number of components in the Gaussian mixture model
| size_t nIterations |
Number of iterations in every short EM run
| size_t nTrials |
Number of trials of short EM runs
| size_t seed |
Seed for randomly generating data points to start the initialization of short EM
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