Introduction to Data Mining, Second Edition

Dr Pang-Ning Tan is a Professor in the Department of Computer Science and Engineering at Michigan State University. He received his M.S. degree in Physics and Ph.D. degree in Computer Science from University of Minnesota. His research interests focus on the development of novel data mining algorithms for a broad range of applications, including climate and ecological sciences, cybersecurity, and network analysis. He has published more than 130 technical papers in the area of data mining, including top conferences and journals such as KDD, ICDM, SDM, CIKM, and TKDE.Dr. Michael Steinbach is a Research Scientist in the department of Computer Science and Engineering at the University of Minnesota, from which he earned a B.S. degree in Mathematics, an M.S. degree in Statistics, and M.S. and Ph.D. degrees in Computer Science. His research interests are in the areas of data mining, machine learning, and statistical learning and its applications to fields, such as climate, biology, and medicine. This research has resulted in more than 100 papers published in the proceedings of major data mining conferences or computer science or domain journals. Previous to his academic career, he held a variety of software engineering, analysis, and design positions in industry at Silicon Biology, Racotek, and NCR.Dr. Anuj Karpatne is a Post Doctoral Associate in the Department of Computer Science and Engineering at the University of Minnesota. He received his M.Tech in Mathematics and Computing from the Indian Institute of Technology Delhi, and a Ph.D. in Computer Science at the University of Minnesota under the guidance of Prof. Vipin Kumar. His research interests lie in the development of data mining and machine learning algorithms for solving scientific and socially relevant problems in varied disciplines such as climate science, hydrology, and healthcare. His research has been published at top-tier journals and conferences such as SDM, ICDM, KDD, NIPS, TKDE, and ACM Computing Surveys.

出版者:Pearson

作者:Pang-Ning Tan

页数:864

出版时间:2018-1-4

价格:USD 126.65

装帧:Hardcover

isbn号码:9780133128901

图书标签:数据挖掘机器学习数据科学Data_Science计算机科学英文原版数据分析USC567

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Introduction to Data Mining, 2nd Edition, gives a comprehensive overview of the background and general themes of data mining and is designed to be useful to students, instructors, researchers, and professionals. Presented in a clear and accessible way, the book outlines fundamental concepts and algorithms for each topic, thus providing the reader with the necessary background for the application of data mining to real problems. The text helps readers understand the nuances of the subject, and includes important sections on classification, association analysis, and cluster analysis. This edition improves on the first iteration of the book, published over a decade ago, by addressing the significant changes in the industry as a result of advanced technology and data growth.

读后感

我是拿这本书当作课程书的，这本书基本上涵盖了数据挖掘的许多经典算法，分类，聚类，关联规则。比较适合对数据挖掘感兴趣的人，这本书看完之后基本上就可以进行对数据的分析，挖掘了。然而这仅仅是一门入门书，对于理论部分并没有做过多的解释。如果想进一步的了解理论知识，...  

统计学经典入门书籍，对数据处理、分类、相关分析、聚类等方面做了事无巨细的讲解，兼顾通俗性和理论推导，浏览一遍目录就会发现，这不就是机器学习嘛！ 看这书名一开始以为这只是一本讲数据抓取、数据分析的书籍，这比市面上一些夸夸其谈机器学习、人工智能的书要低调很多，而...  

Chapter2 和 Chapter3 一大堆废话，基本都是初中高中教的！！！好像跳过这些章节！！！ Chapter2 和 Chapter3 一大堆废话，基本都是初中高中教的！！！好像跳过这些章节！！！ Chapter2 和 Chapter3 一大堆废话，基本都是初中高中教的！！！好像跳过这些章节！！！  

看我截图吧 http://weibo.com/1677386655/zu8O4ci9O therefore, if we compute the k-dist for all the data points for some k, sort them in increasing order, and ther plot the sorted values, we expect to see a sharp change at the value of k-dist that correspon...  

我是拿这本书当作课程书的，这本书基本上涵盖了数据挖掘的许多经典算法，分类，聚类，关联规则。比较适合对数据挖掘感兴趣的人，这本书看完之后基本上就可以进行对数据的分析，挖掘了。然而这仅仅是一门入门书，对于理论部分并没有做过多的解释。如果想进一步的了解理论知识，...