Searched refs:precisions_chol (Results 1 – 1 of 1) sorted by relevance
| /dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/mixture/ |
| H A D | _gaussian_mixture.py | 327 precisions_chol = np.empty((n_components, n_features, n_features))
333 precisions_chol[k] = linalg.solve_triangular(
342 precisions_chol = linalg.solve_triangular(
348 precisions_chol = 1.0 / np.sqrt(covariances)
349 return precisions_chol
394 def _estimate_log_gaussian_prob(X, means, precisions_chol, covariance_type): argument
422 log_det = _compute_log_det_cholesky(precisions_chol, covariance_type, n_features)
426 for k, (mu, prec_chol) in enumerate(zip(means, precisions_chol)):
433 y = np.dot(X, precisions_chol) - np.dot(mu, precisions_chol)
437 precisions = precisions_chol ** 2
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