learning.utils¶
Module: learning.utils¶
Functions¶
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selectinf.learning.utils.full_model_inference(X, y, truth, selection_algorithm, sampler, success_params=(1, 1), fit_probability=<function gbm_fit_sk>, fit_args={'n_estimators': 500}, alpha=0.1, B=2000, naive=True, learner_klass=<class 'selectinf.learning.learners.mixture_learner'>, features=None, how_many=None)[source]¶
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selectinf.learning.utils.liu_inference(X, y, lam, dispersion, truth, alpha=0.1, approximate_inverse=None)[source]¶
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selectinf.learning.utils.naive_full_model_inference(X, y, dispersion, truth, observed_set, alpha=0.1, how_many=None)[source]¶
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selectinf.learning.utils.naive_partial_model_inference(X, y, dispersion, truth, observed_set, alpha=0.1)[source]¶
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selectinf.learning.utils.partial_model_inference(X, y, truth, selection_algorithm, sampler, success_params=(1, 1), fit_probability=<function gbm_fit_sk>, fit_args={'n_estimators': 500}, alpha=0.1, B=2000, naive=True, learner_klass=<class 'selectinf.learning.learners.mixture_learner'>)[source]¶