Machine learning versus statistical modeling
Copyright policy )Machine learning versus statistical modeling
This is a discussion of the following papers: “Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory” by Jochen Kruppa, Yufeng Liu, Gérard Biau, Michael Kohler, Inke R. König, James D. Malley, and Andreas Ziegler; and “Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications” by Jochen Kruppa, Yufeng Liu, Hans‐Christian Diener, Theresa Holste, Christian Weimar, Inke R. König, and Andreas Ziegler.
Stochastic Processes, Biometry, Models, Statistical, Classification and discrimination; cluster analysis (statistical aspects), logistic regression, Learning and adaptive systems in artificial intelligence, Reproducibility of Results, prediction, tuning parameters, transportability, Applications of statistics to biology and medical sciences; meta analysis, Artificial Intelligence, Nonparametric regression and quantile regression, reproducibility, Algorithms
Stochastic Processes, Biometry, Models, Statistical, Classification and discrimination; cluster analysis (statistical aspects), logistic regression, Learning and adaptive systems in artificial intelligence, Reproducibility of Results, prediction, tuning parameters, transportability, Applications of statistics to biology and medical sciences; meta analysis, Artificial Intelligence, Nonparametric regression and quantile regression, reproducibility, Algorithms
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Citations provided by BIP!Popularity provided by BIP!