Berry And Linoff Data Mining Techniques
- Berry and linhoff data mining techniques with explanation
- Berry and linoff data mining techniques de base
- Data Mining Techniques: Marketing, Sales and Customer Support by Gordon S. Linoff, Michael J. Berry (Hardback, 1997) for sale online | eBay
Error rating book. Refresh and try again. Rate this book Clear rating Be the first to ask a question about Data Mining Techniques Average rating 4. 07 · 70 ratings 3 reviews | Start your review of Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management A very decent overview of data mining techniques and decent examples in between. This may not be a book for you, however, if you don't have some experience in data mining or you aren't someone who naturally finds general topics on data mining to be thought provoking. The explanations and examples put the theory throughout the book to practical use... read some case studies, not very interested This had some good concepts that I could utilize in my work, namely how to deal with null values, customer signatures, intros into regression, clustering, decision trees. If you like books and love to build cool products, we may be looking for you. Learn more » Angie Thomas was as stunned as her fans when she was spurred to write a prequel to The Hate U Give, her blockbuster 2017 YA debut inspired by... 27 likes · 0 comments
Berry and linhoff data mining techniques with explanation
Technical topics are illustrated with case studies and practical real-world examples drawn from the authors' experiences, and every chapter contains valuable tips for practitioners. Among the techniques newly covered, or covered in greater depth, are linear and logistic regression models, incremental response (uplift) modeling, naive Bayesian models, table lookup models, similarity models, radial basis function networks, expectation maximization (EM) clustering, and swarm intelligence. New chapters are devoted to data preparation, derived variables, principal components and other variable reduction techniques, and text mining. -- After establishing the business context with an overview of data mining applications, and introducing aspects of data mining methodology common to all data mining projects, the book covers each important data mining technique in detail. --Book Jacket. … ( more) ▾ Member recommendations ▾ Will you like it? Loading... Sign up for LibraryThing to find out whether you'll like this book.
Язык: Английский (эта книга не перевод) Опубликовано здесь: 2017-12-26 The leading introductory book on data mining, fully updated and revised! When Berry and Linoff wrote the first edition of Data Mining Techniques in the late 1990s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. This new edition—more than 50% new and revised— is a significant update from the previous one, and shows you how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company.
Berry and linoff data mining techniques de base
CRC for Integrated Engineering Asset Management Brisbane Australia 2. School of Computer and Information Science University of South Australia Mawson Lakes Australia
Content analysis research aims to describe in detail the range of data mining technology differences and overlap across academic disciplines. Related Articles: Comparing Data Mining Techniques in HIV Testing Prediction Tesfay Gidey Hailu DOI: 10. 4236/iim. 2015. 73014 5, 784 Downloads 7, 262 Views Citations Pub. Date: May 28, 2015 Findings Seminal Papers Using Data Mining Techniques Alexander Báez Hernández, Debrayan Bravo Hidalgo 10. 4236/jss. 2020. 89023 72 Downloads 305 Views September 25, 2020 Big Data Analytics of Taxi Operations in New York City Yuxin Tang 10. 4236/ajor. 2019. 94012 556 Downloads 1, 140 Views Citations July 31, 2019 A Data Mining Based Approach to Customer Behaviour in an Electronic Settings A. Tope-Oke, C. A. Afolalu, O. Omofade 10. 4236/jcc. 75004 422 Downloads 920 Views Estimating the Size of the Methamphetamine-Using Population in New York City Using Network Sampling Techniques Kirk Dombrowski, Bilal Khan, Travis Wendel, Katherine McLean, Evan Misshula, Ric Curtis 10.
Data Mining Techniques: Marketing, Sales and Customer Support by Gordon S. Linoff, Michael J. Berry (Hardback, 1997) for sale online | eBay
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