*R and Data Mining* introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amount
Data Mining || Text Mining
β Scribed by Cios, Krzysztof J.
- Book ID
- 120259192
- Publisher
- Springer US
- Year
- 2007
- Tongue
- English
- Weight
- 507 KB
- Edition
- 2007
- Category
- Article
- ISBN
- 0387333339
No coin nor oath required. For personal study only.
β¦ Synopsis
this Comprehensive Textbook On Data Mining Details The Unique Steps Of The Knowledge Discovery Process That Prescribe The Sequence In Which Data Mining Projects Should Be Performed. Data Mining Offers An Authoritative Treatment Of All Development Phases From Problem And Data Understanding Through Data Preprocessing To Deployment Of The Results. This Knowledge Discovery Approach Is What Distinguishes This Book From Other Texts In The Area. It Concentrates On Data Preparation, Clustering And Association Rule Learning (required For Processing Unsupervised Data), Decision Trees, Rule Induction Algorithms, Neural Networks, And Many Other Data Mining Methods, Focusing Predominantly On Those Which Have Proven Successful In Data Mining Projects.
based Upon The Authorsβ Previous Successful Book On Data Mining And Knowledge Discovery, This New Volume Has Been Extensively Expanded, Making It An Effective Instructional Tool For Advanced-level Undergraduate And Graduate Courses. This Book Offers:
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a Suite Of Exercises At The End Of Every Chapter, Designed To Enhance The Readerβs Understanding Of The Theory And Proficiency With The Tools Presented
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links To All-inclusive Instructional Presentations For Each Chapter To Ensure Easy Use In Classroom Teaching
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extensive Appendices Covering Relevant Mathematical Material For Convenient Look-up
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methods For Addressing Issues Related To Data Privacy And Security Within The Context Of Data Mining, Enabling The Reader To Balance Potentially Conflicting Aims
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summaries And Bibliographical Notes For Each Chapter, Providing A Broader Perspective Of The Concepts And Methods Described
researchers, Practitioners And Students Are Certain To Consider This Volume An Indispensable Resource In Successfully Accomplishing The Goals Of Their Data Mining Projects.
π SIMILAR VOLUMES
Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche