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Searched defs:covariance_type (Results 1 – 8 of 8) sorted by relevance

/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/mixture/
H A D_gaussian_mixture.py78 def _check_precision_positivity(precision, covariance_type): argument
84 def _check_precision_matrix(precision, covariance_type): argument
94 def _check_precisions_full(precisions, covariance_type): argument
100 def _check_precisions(precisions, covariance_type, n_components, n_features): argument
260 def _estimate_gaussian_parameters(X, resp, reg_covar, covariance_type): argument
300 def _compute_precision_cholesky(covariances, covariance_type): argument
354 def _compute_log_det_cholesky(matrix_chol, covariance_type, n_features): argument
394 def _estimate_log_gaussian_prob(X, means, precisions_chol, covariance_type): argument
636 covariance_type="full", argument
H A D_bayesian_mixture.py343 covariance_type="full", argument
/dports/science/ALPSCore/ALPSCore-2.2.0/utilities/include/alps/type_traits/
H A Dcovariance_type.hpp31 struct covariance_type struct
39 >::type type;
/dports/math/octave-forge-stk/stk/inst/model/prior_struct/
H A Dstk_model.m64 covariance_type = str2func (covariance_type); variable
70 covariance_type = @stk_materncov_iso; variable
/dports/math/octave-forge-stk/stk/inst/param/estim/
H A Dstk_param_getdefaultbounds.m94 covariance_type = func2str (covariance_type); variable
/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/mixture/tests/
H A Dtest_gaussian_mixture.py41 def generate_data(n_samples, n_features, weights, means, precisions, covariance_type): argument
/dports/science/ALPSCore/ALPSCore-2.2.0/accumulators/include/alps/accumulators/feature/
H A Dmax_num_binning.hpp108 template<typename T> struct covariance_type struct
/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/duration/
H A Dhazard_regression.py1406 def __init__(self, model, params, cov_params, scale=1., covariance_type="naive"): argument