Data mining and statistics for decision making / Stéphane Tufféry.
نوع المادة : نصالسلاسل:Wiley series in computational statisticsالناشر:Chichester, West Sussex ; Hoboken, NJ. : Wiley, 2011وصف:xxiv, 689 pages. : illustration ; 25 cmنوع المحتوى:- text
- unmediated
- volume
- 9780470688298 (hbk.)
- 9780470979167 (epdf.)
- 9780470979174 (obk.)
- 9780470979280 (epub.)
- QA76.9.D343 T84 2011
نوع المادة | المكتبة الحالية | رقم الطلب | رقم النسخة | حالة | تاريخ الإستحقاق | الباركود | |
---|---|---|---|---|---|---|---|
كتاب | UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة | QA76.9.D343 T84 2011 (إستعراض الرف(يفتح أدناه)) | C.1 | Library Use Only | داخل المكتبة فقط | 30010011128839 |
Browsing UAE Federation Library | مكتبة اتحاد الإمارات shelves, Shelving location: General Collection | المجموعات العامة إغلاق مستعرض الرف(يخفي مستعرض الرف)
QA76.9.D343 S74125 2018 الكل يكذب : البيانات الضخمة، والبيانات الحديثة وقدرة الإنترنت على اكتشاف الخفايا / | QA76.9.D343 S74125 2018 الكل يكذب : البيانات الضخمة، والبيانات الحديثة وقدرة الإنترنت على اكتشاف الخفايا / | QA76.9.D343 S74125 2018 الكل يكذب : البيانات الضخمة، والبيانات الحديثة وقدرة الإنترنت على اكتشاف الخفايا / | QA76.9.D343 T84 2011 Data mining and statistics for decision making / | QA76.9.D343 V57 2004 Visual and spatial analysis : advances in data mining reasoning, and problem solving / | QA76.9.D348 T653 2000 Disaster recovery planning : strategies for protecting critical information / | QA76.9.D35 K558 2016 Basic concepts in data structures / |
Includes bibliographical references and index.
Overview of data mining -- The development of a data mining study -- Data exploration and preparation -- Using commercial data -- Statistical and data mining software -- An outline of data mining methods -- Factor analysis -- Neural networks -- Cluster analysis -- Association analysis -- Classification and prediction methods -- An application of data mining: scoring -- Factors for success in a data mining project -- Text mining -- Web mining -- Appendix A: Elements of statistics -- Appendix B: further reading.
"This practical guide to understanding and implementing data mining techniques discusses traditional methods--cluster analysis, factor analysis, linear regression, PLS regression, and generalized linear models--and recent methods--bagging and boosting, decision trees, neural networks, support vector machines, and genetic algorithm. The book focuses largely on credit scoring, one of the most common applications of predictive techniques, but also includes other descriptive techniques, such as customer segmentation. It also covers data mining with R, provides a comparison of SAS and SPSS, and includes an appendix presenting the necessary statistical background"-- Provided by publisher.
"Data Mining is a practical guide to understanding and implementing data mining techniques, featuring traditional methods such as cluster analysis, factor analysis, linear regression, PLS regression and generalised linear models"-- Provided by publisher.