Parameters of the EM for GMM algorithm.
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Parameters of the EM for GMM algorithm
double getAccuracyThreshold |
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Retrieves the threshold for the termination of the algorithm
- Returns
- Threshold for the termination of the algorithm
Retrieves identifier of covariance type in the EM for GMM algorithm
- Returns
- identifier of covariance type in the EM for GMM algorithm
long getMaxIterations |
( |
| ) |
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Retrieves the maximal number of iterations
- Returns
- Maximal number of iterations
Retrieves the number of components in the Gaussian mixture model
- Returns
- Number of components
double getRegularizationFactor |
( |
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Retrieves the factor for covariance regularization value in case of ill-conditional data
- Returns
- Factor for covariance regularization value in case of ill-conditional data
void setAccuracyThreshold |
( |
double |
accuracyThreshold | ) |
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Sets the threshold for the termination of the algorithm
- Parameters
-
accuracyThreshold | Threshold for the termination of the algorithm |
Sets the identifier of covariance type in the EM for GMM algorithm
- Parameters
-
covarianceStorage | identifier of covariance type in the EM for GMM algorithm |
void setMaxIterations |
( |
long |
maxIterations | ) |
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Sets the maximal number of iterations
- Parameters
-
maxIterations | Maximal number of iterations |
void setNComponents |
( |
long |
nComponents | ) |
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Sets the number of components in the Gaussian mixture model
- Parameters
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nComponents | Number of components in the Gaussian mixture model |
void setRegularizationFactor |
( |
double |
regularizationFactor | ) |
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Sets the factor for covariance regularization value in case of ill-conditional data
- Parameters
-
regularizationFactor | Factor for covariance regularization value in case of ill-conditional data |
The documentation for this class was generated from the following file: