| 书目名称 | Modern Data Mining Algorithms in C++ and CUDA C |
| 副标题 | Recent Developments |
| 编辑 | Timothy Masters |
| 视频video | http://file.papertrans.cn/638/637077/637077.mp4 |
| 概述 | A novel expert-driven data-mining approach to algorithms in C++ and CUDA C.Author has been developing and using algorithms for over 20 years.Data mining is an important topic in big data and data scie |
| 图书封面 |  |
| 描述 | .Discover a variety of data-mining algorithms that are useful for selecting small sets of important features from among unwieldy masses of candidates, or extracting useful features from measured variables. ..As a serious data miner you will often be faced with thousands of candidate features for your prediction or classification application, with most of the features being of little or no value. You’ll know that many of these features may be useful only in combination with certain other features while being practically worthless alone or in combination with most others. Some features may have enormous predictive power, but only within a small, specialized area of the feature space. The problems that plague modern data miners are endless. This book helps you solve this problem by presenting modern feature selection techniques and the code to implement them. Some of these techniques are:.Forward selection componentanalysis..Local feature selection.Linking features and a targetwith a hidden Markov model.Improvements on traditionalstepwise selection.Nominal-to-ordinalconversion. .All algorithms are intuitively justified and supported by the relevant equations and explanatory material. |
| 出版日期 | Book 2020 |
| 关键词 | C++; Data Mining; algorithms; CUDA C; big data; programming; mining; software; code; technique; data science; e |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4842-5988-7 |
| isbn_softcover | 978-1-4842-5987-0 |
| isbn_ebook | 978-1-4842-5988-7 |
| copyright | Timothy Masters 2020 |
|Archiver|手机版|小黑屋|
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