Results 291 to 300 of about 2,065,553 (347)

Machine‐learning‐enhanced tail end prediction of structural response statistics in earthquake engineering

Earthquake engineering & structural dynamics (Print), 2021
Evaluating the response statistics of nonlinear structures constitutes a key issue in engineering design. Hereby, the Monte Carlo method has proven useful, although the computational cost turns out to be considerably high.
Denny Thaler, M. Stoffel, B. Markert, F. Bamer   +3 more
semanticscholar   +1 more source

Machine Learning and Statistics: The Interface

Journal of the American Statistical Association, 1998
Statistical Properties of Tree-Based Approaches to Classification The Decision Tree Algorithm CAL5 Based on a Statistical Approach to its Splitting Algorithm Probabilistic Symbolic Classifiers: An Empirical Comparison from a Statistical Perspective A Multistrategy Approach to Learning Multiple Dependent Concepts Quality of Decision Rules - Definition ...
Michael J. Turmon, Gholamreza Nakhaeizadeh, Charles C. Taylor   +2 more
openaire   +2 more sources

Machine learning versus statistical modeling

Biometrical Journal, 2014
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
Matthias Schmid, Anne-Laure Boulesteix
openaire   +3 more sources

Statistical Machine Learning for Researchers

2023
This workshop is designed to empower researchers with the fundamentals of machine learning using R. Participants will learn the key principles that make machine learning so effective, powering the modern AI and deep learning revolution. Through hands-on exercises, participants will gain experience applying a variety of flexible and scalable statistical
openaire   +1 more source

In-game behaviour analysis of football players using machine learning techniques based on player statistics

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, Moisés Marquina, J. Coterón, Asier Rodríguez-González, Sergio Luengo-Sanchez   +4 more
semanticscholar   +1 more source

Challenges in Statistical Machine Learning

2005
Machine learning and statistics are one and the same discipline, with different communities of researchers attacking essentially the same fundamental problems from different perspectives. In this note we briefly describe some current challenges in the fi eld of statistical machine learning that cut across the communities.
Lafferty, John D., Wasserman, Larry
openaire   +1 more source

Machine Learning Based of Cardiac Attack Prediction Application

2023 International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT), 2023
The biggest cause of mortality in high-income nations right now is cardiovascular disease, and by 2030, it's expected to overtake all other causes of death worldwide.
Kishore Kanna R, Pradeep Kumar, A. Ambikapathy, A. Singh, Mustafa Asaad Hussein   +4 more
semanticscholar   +1 more source

Statistics, Data Mining, and Machine Learning in Astronomy

, 2019
Statistics, 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, A. Connolly, J. Vanderplas, Alexander Gray   +3 more
semanticscholar   +1 more source

Multinomial conjunctoid statistical learning machines

[1988] The 15th Annual International Symposium on Computer Architecture. Conference Proceedings, 1988
Multinomial Conjunctoids are supervised statistical modules that learn the relationships among binary events. The multinomial conjunctoid algorithm precludes the following problems that occur in existing feedforward multi-layered neural networks: (a) existing networks often cannot determine underlying neural architectures, for example how many hidden ...
Robert J. Jannarone, T. Chen, Yoshiyasu Takefuji, Yong B. Cho   +3 more
openaire   +2 more sources

Safe machine learning

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
semanticscholar   +1 more source