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Machine learning versus statistical modeling
Biometrical Journal, 2014This 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
Boulesteix, Anne-Laure, Schmid, Matthias
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Statistics, Data Mining, and Machine Learning in Astronomy
, 2019Statistics, Data Mining, and Machine Learning in Astronomy is the essential introduction to the statistical methods needed to analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark ...
Ž. Ivezić +3 more
semanticscholar +1 more source
International journal of sports science & coaching, 2020
The purpose of this research was to determine the on-field playing positions of a group of football players based on their technical-tactical behaviour using machine learning algorithms.
Abraham García-Aliaga +4 more
semanticscholar +1 more source
The purpose of this research was to determine the on-field playing positions of a group of football players based on their technical-tactical behaviour using machine learning algorithms.
Abraham García-Aliaga +4 more
semanticscholar +1 more source
Statistics, machine learning and deep learning for population genetic inference
, 2021Xinghu Qin
semanticscholar +2 more sources
Statistics (Berlin)
The rapid development of artificial intelligence applications based on machine learning is creating not only many opportunities but also risks. The recent regulatory and political debate, at the international level, emphasizes the urgent need to develop ...
Paolo Giudici
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The rapid development of artificial intelligence applications based on machine learning is creating not only many opportunities but also risks. The recent regulatory and political debate, at the international level, emphasizes the urgent need to develop ...
Paolo Giudici
semanticscholar +1 more source
2019
AbstractThis chapter describes in detail how the main techniques of statistical machine learning can be constructed from the components described in earlier chapters. It presents these concepts in a way which demonstrates how these techniques can be viewed as special cases of a more general probabilistic model which we fit to some data.
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AbstractThis chapter describes in detail how the main techniques of statistical machine learning can be constructed from the components described in earlier chapters. It presents these concepts in a way which demonstrates how these techniques can be viewed as special cases of a more general probabilistic model which we fit to some data.
openaire +1 more source
Science of the Total Environment, 2019
The present study is carried out in the context of the continuous increase, worldwide, of the number of flash-floods phenomena. Also, there is an evident increase of the size of the damages caused by these hazards.
R. Costache, Haoyuan Hong, Q. Pham
semanticscholar +1 more source
The present study is carried out in the context of the continuous increase, worldwide, of the number of flash-floods phenomena. Also, there is an evident increase of the size of the damages caused by these hazards.
R. Costache, Haoyuan Hong, Q. Pham
semanticscholar +1 more source
, 2020
The global warming and climate changes determined a considerable increase in the frequency of floods and their related damages. Therefore, the high accuracy prediction of flood susceptible areas plays a key role in flood warnings and risk reduction.
R. Costache +6 more
semanticscholar +1 more source
The global warming and climate changes determined a considerable increase in the frequency of floods and their related damages. Therefore, the high accuracy prediction of flood susceptible areas plays a key role in flood warnings and risk reduction.
R. Costache +6 more
semanticscholar +1 more source