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Code_chap_23_logistic_regression_regularization
Code_chap_23_logistic_regression_regularization PublicAlgorithmes d’apprentissage et modèles statistiques: Un exemple de régression logistique régularisée et de validation croisée pour prédire le décrochage scolaire
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- stepmix Public
A Python package following the scikit-learn API for model-based clustering and generalized mixture modeling (latent class/profile analysis) of continuous and categorical data. StepMix handles missing values through Full Information Maximum Likelihood (FIML) and provides multiple stepwise Expectation-Maximization (EM) estimation methods.
Labo-Lacourse/stepmix’s past year of commit activity - RMLCA-with-StepMix Public
Labo-Lacourse/RMLCA-with-StepMix’s past year of commit activity - Code_chap_23_logistic_regression_regularization Public
Algorithmes d’apprentissage et modèles statistiques: Un exemple de régression logistique régularisée et de validation croisée pour prédire le décrochage scolaire
Labo-Lacourse/Code_chap_23_logistic_regression_regularization’s past year of commit activity - Praxis-Module-1 Public
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