{"product_id":"outlier-analysis-paperback","title":"Outlier Analysis - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eCharu C. Aggarwal\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003eProvides all the fundamental algorithms for outlier analysis in great detail including those for advanced data types, including specific insights into when and why particular algorithms work effectively\u003cbr\u003eDiscusses the latest ideas in the field such as outlier ensembles, matrix factorization, kernel methods, and neural networks\u003cbr\u003eCovers theoretical and practical aspects of outlier analysis including specific practical details for accurate implementation\u003cbr\u003eOffers numerous illustrations and exercises for classroom teaching, including a solution manual\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003eThis book provides comprehensive coverage of the field of outlier analysis from a computer science point of view. It integrates methods from data mining, machine learning, and statistics within the computational framework and therefore appeals to multiple communities. The chapters of this book can be organized into three categories: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eBasic algorithms: Chapters 1 through 7 discuss the fundamental algorithms for outlier analysis, including probabilistic and statistical methods, linear methods, proximity-based methods, high-dimensional (subspace) methods, ensemble methods, and supervised methods.\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eDomain-specific methods: Chapters 8 through 12 discuss outlier detection algorithms for various domains of data, such as text, categorical data, time-series data, discrete sequence data, spatial data, and network data.\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eApplications: Chapter 13 is devoted to various applications of outlier analysis. Some guidance is also provided for the practitioner.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003eThe second edition of this book is more detailed and is written to appeal to both researchers and practitioners. Significant new material has been added on topics such as kernel methods, one-class support-vector machines, matrix factorization, neural networks, outlier ensembles, time-series methods, and subspace methods. It is written as a textbook and can be used for classroom teaching.\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003eCharu C. Aggarwal is a Distinguished Research Staff Member (DRSM) at the IBM T. J. Watson Research Center in Yorktown Heights, New York. He completed his undergraduate degree in Computer Science from the Indian Institute of Technology at Kanpur in 1993 and his Ph.D. in Operations Research from the Massachusetts Institute of Technology in 1996. He has published more than 300 papers in refereed conferences and journals, and has applied for or been granted more than 80 patents. He is author or editor of 15 books, including textbooks on data mining, recommender systems, and outlier analysis. Because of the commercial value of his patents, he has thrice been designated a Master Inventor at IBM. He has received several internal and external awards, including the EDBT Test-of-Time Award (2014) and the IEEE ICDM Research Contributions Award (2015). He has also served as program or general chair of many major conferences in data mining. He is a fellow of the SIAM, ACM, and the IEEE, for \"contributions to knowledge discovery and data mining algorithms.\"\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 466\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.98 x 10 x 7 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e May 04, 2018\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47212917195001,"sku":"9783319837727","price":97.18,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/UjRaV2JDZS8vS3hYUlltL3lwUDFpQT09.webp?v=1768098981","url":"https:\/\/bookscloud.io\/products\/outlier-analysis-paperback","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}