| 书目名称 | Meta-Learning in Decision Tree Induction |
| 编辑 | Krzysztof Grąbczewski |
| 视频video | |
| 概述 | Presents a general meta-learning approach which is applicable to a variety of machine learning algorithms.Focuses on different variants of decision tree induction.Details the long and complex road fro |
| 丛书名称 | Studies in Computational Intelligence |
| 图书封面 |  |
| 描述 | .The book focuses on different variants of decision tree induction but also describes the meta-learning approach in general which is applicable to other types of machine learning algorithms. The book discusses different variants of decision tree induction and represents a useful source of information to readers wishing to review some of the techniques used in decision tree learning, as well as different ensemble methods that involve decision trees. It is shown that the knowledge of different components used within decision tree learning needs to be systematized to enable the system to generate and evaluate different variants of machine learning algorithms with the aim of identifying the top-most performers or potentially the best one. A unified view of decision tree learning enables to emulate different decision tree algorithms simply by setting certain parameters. As meta-learning requires running many different processes with the aim of obtaining performance results, a detailed description of the experimental methodology and evaluation framework is provided. Meta-learning is discussed in great detail in the second half of the book. The exposition starts by presenting a comprehen |
| 出版日期 | Book 2014 |
| 关键词 | Computational Intelligence; Machine Learning Decision Tree Induction; Meta-Learning |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-00960-5 |
| isbn_softcover | 978-3-319-37723-0 |
| isbn_ebook | 978-3-319-00960-5Series ISSN 1860-949X Series E-ISSN 1860-9503 |
| issn_series | 1860-949X |
| copyright | Springer International Publishing Switzerland 2014 |
发表于 2025-3-21 19:56:44
