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	Browse All Reviews > Software (D) > Software Engineering (D.2) > Software/Program Verification (D.2.4) > Statistical Methods (D.2.4...)     Options: All Media Types Journals Proceedings Div Books Whole Books Other Date Reviewed Title Author Publisher Published Date Descending Ascending     1-9 of 9 Reviews about "Statistical Methods (D.2.4...)": Date Reviewed    Introduction to statistical and machine learning methods for data science Pinheiro C., Patetta M., SAS Institute Inc., Cary, NC, 2021.  Type: Book (1953329608) With this book, Dr. Carlos Pinheiro and Mike Patetta present a comprehensive and detailed exploration of data science techniques and applications. Introduction to statistical and machine learning methods for data science offers a broad over... Jan 15 2024    Predicting the unknown: the history and future of data science and artificial intelligence Kampakis S., Apress, New York, NY, 2023. 281 pp.  Type: Book (1484295048) Physicist Niels Bohr observed: “Prediction is very difficult, especially if it’s about the future!” Despite that warning, scientists, politicians, journalists, doctors, economists--professionals in nearly every knowledge ... Nov 29 2023   Statistical methods for data analysis: with applications in particle physics (3rd ed.) Lista L., Springer International Publishing, Cham, Switzerland, 2023. 334 pp.  Type: Book (9783031199332) Statistical methods for data analysis explores possibilities for artificial intelligence (AI), statistics, and data science in particle physics. Although the title of the book does not mention AI, the content of the book applies some AI con... Aug 8 2023   Predictive statistics: analysis and inference beyond models Clarke B., Clarke J., Cambridge University Press, New York, NY, 2018. 656 pp.  Type: Book (978-1-107028-28-9) As stated in the preface, Predictive statistics “is an attempt to focus more heavily on the data than the formalism and to focus more heavily on the performance of predictors rather than the fit or physical interpretat... Dec 24 2018   A computational approach to nonparametric regression: bootstrapping CMARS method Yazıcı C., Yerlikaya-Özkurt F., Batmaz İ. Machine Learning 101(1-3): 211-230, 2015.  Type: Article A well-defined model can relate phenomena and conclusions, which can enhance our understanding of knowledge and help our work decisively. In statistics, one popular research topic is to formulate mathematical models using existing data... Dec 9 2015   Firms’ involvement in open source projects: a trade-off between software structural quality and popularity Capra E., Francalanci C., Merlo F., Rossi-Lamastra C. Journal of Systems and Software 84(1): 144-161, 2011.  Type: Article This paper explores the impact of industry involvement on open-source projects. The authors make two claims, backed up by statistical models using SourceForge data. The first claim is that industrial involvement that starts at the begi... Aug 1 2011   A framework for efficient regression tests on database applications Haftmann F., Kossmann D., Lo E. The VLDB Journal: The International Journal on Very Large Data Bases 16(1): 145-164, 2007.  Type: Article Regression testing is an important task in a software development or maintenance process. It ensures that modified software does not break any existing functionality. From a cost perspective, regression testing is expensive and time co... Mar 27 2008   Impartial evaluation in software reliability practice Chang W., Jeng S. Journal of Systems and Software 76(2): 99-110, 2005.  Type: Article In today’s world, software is used almost everywhere, from mission-critical applications, like rocket technology, to cartoon games. The necessity of certifying the reliability of software products and services has gained ... Sep 14 2005   Software failure prediction based on a Markov Bayesian network model Bai C., Hu Q., Xie M., Ng S. Journal of Systems and Software 74(3): 275-282, 2005.  Type: Article In this paper, the authors predict software failure using their Markov Bayesian network model (MBN) when the parameters in the related distributions are not available. This paper is an extension of another paper [1].... Jun 24 2005       Display 510152550100 per page
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