Data mining : know it all
Soumen Chakrabarti; Earl Cox; Eibe Frank; Ralf Güting; Jiawei Han; Xia Jiang; Micheline Kamber; Sam Lightstone; Thomas Nadeau; Richard Neapolitan; Dorian Pyle; Mamdouh Refaat; Markus Schneider; Toby Teorey; Ian Witten; Safari, an O’Reilly Media Companyقیمت نهایی
۴۰٬۰۰۰ تومان۴۹٬۰۰۰ تومان۱۸٪ تخفیف
- تخفیف زماندار−۹٬۰۰۰ تومان
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نسخه اصلی و اورجینال
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تحویل فوری
پرداخت امن
ضمانت فایل
پشتیبانی
مشخصات کتاب
- سال انتشار
- ۲۰۰۹
- فرمت
- زبان
- انگلیسی
- تعداد صفحات
- ۴ صفحه
- حجم فایل
- ۲٫۴ مگابایت
- شابک
- 9780080877884، 9780123746290، 9781282711129، 0080877885، 0123746299، 1282711121
دربارهٔ کتاب
This book brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. It consolidates both introductory and advanced topics, thereby covering the gamut of data mining and machine learning tactics ? from data integration and pre-processing, to fundamental algorithms, to optimization techniques and web mining methodology. The proposed book expertly combines the finest data mining material from the Morgan Kaufmann portfolio. Individual chapters are derived from a select group of MK books authored by the best and brightest in the field. These chapters are combined into one comprehensive volume in a way that allows it to be used as a reference work for those interested in new and developing aspects of data mining. This book represents a quick and efficient way to unite valuable content from leading data mining experts, thereby creating a definitive, one-stop-shopping opportunity for customers to receive the information they would otherwise need to round up from separate sources. Chapters contributed by various recognized experts in the field let the reader remain up to date and fully informed from multiple viewpoints. Presents multiple methods of analysis and algorithmic problem-solving techniques, enhancing the reader’s technical expertise and ability to implement practical solutions. Coverage of both theory and practice brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. The need for a laboratory and field manual to assist with the evaluation of juvenile skeletal material is long overdue. This resource is essential for the practising osteoarchaeologist and forensic anthropologist who requires a quick, reliable and easy-to-use reference to aid in the identification, siding and aging of juvenile osseous material. While excellent reference books on juvenile osteology are currently available, no pre-existing source adequately fills this particular niche in the market. This field manual is designed with practicality as its primary directive. Descriptions of each bone contain 1) morphological characteristics useful for identification, 2) other elements with which the bone may be confused, 2) tips for siding, 3) illustrations of varying developmental phases, 4) data useful for ageing, and 5) a summary of developmental timings. Concise, bullet-style descriptions assist with quick retrieval of information. Unique to this manual is the presentation of data collected from a variety of populations, utilizing a range of observational methods, as an alternative to providing one overall aging summary that is derived from a compilation of many individual sources. This manual provides a host of data on a variety of populations to enable the user to select the reference most applicable to their needs. The final chapter combines information from each bone to provide a summary of developmental changes occurring at different life stages to act as an immediate 'ready reckoner' for the knowledgeable practitioner. It also provides forms useful for documenting juvenile material and diagrams to help with the recognition of commingled juvenile remains. The manual is a must for anyone responsible for the evaluation of juvenile osseous material through dry bone assessment, radiographs, sonograms, and or CT scans This book brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. It consolidates both introductory and advanced topics, thereby covering the gamut of data mining and machine learning tactics ? from data integration and pre-processing, to fundamental algorithms, to optimization techniques and web mining methodology. The proposed book expertly combines the finest data mining material from the Morgan Kaufmann portfolio. Individual chapters are derived from a select group of MK books authored by the best and brightest in the field. These chapters are combined into one comprehensive volume in a way that allows it to be used as a reference work for those interested in new and developing aspects of data mining. This book represents a quick and efficient way to unite valuable content from leading data mining experts, thereby creating a definitive, one-stop-shopping opportunity for customers to receive the information they would otherwise need to round up from separate sources. Chapters contributed by various recognized experts in the field let the reader remain up to date and fully informed from multiple viewpoints. Presents multiple methods of analysis and algorithmic problem-solving techniques, enhancing the reader's technical expertise and ability to implement practical solutions. Coverage of both theory and practice brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. This book is about data acquisition and integration, data preprocessing, physical design for decision support, warehousing, and OLAP, Algorithms: the basic methods, further techniques in decision analysis, fundamental concepts of genetic algorithms, data structures and algorithms for moving objects types. What's it all about? -- Data acquisition and integration -- Data preprocessing -- Physical design for decision support, warehousing, and OLAP -- Algorithms, the basic methods -- Further techniques in decision analysis -- Fundamental concepts of genetic algorithms -- Data structures and algorithms for moving objects types -- Improving the model -- Social network analysis
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