Mastering Data Mining: The Art and Science of Customer Relationship Management
| Author | : | |
| Rating | : | 4.84 (725 Votes) |
| Asin | : | B003VIWZGK |
| Format Type | : | |
| Number of Pages | : | 278 Pages |
| Publish Date | : | 2017-07-09 |
| Language | : | English |
DESCRIPTION:
. LINOFF gordon@data-miners are the founders of Data Miners Inc., a respected data mining consultancy. When not actively engaged in data mining projects, they present classes and seminars that have been well received around the world. BERRY mjab@data-miners and GORDON S. MICHAEL J. A
"I give it full marks for both content and value for money"(Computer Bulletin - Book of the month, March 2001)
Through the cases, you will learn how to formulate the business problem, analyze the data, evaluate the results, and utilize this information for similar business problems in different industries. After providing the fundamental principles of data mining and customer relationship management, Berry and Linoff share the lessons they have learned through a series of warts-and-all case studies drawn from their experience in a variety of industries, including e-commerce, banking, cataloging, retailing, and telecommunications. A. Linoff offer a case study-based guide to best practices in commerc
Excellent book! This book is an excellent book. The authors explain the various techniques, and show real world examples of their use. Most importantly, they explain the underlying goals of the various techniques, and what to watch out for when using them. I was most relieved to read that I am not alone in having limited success with association rules!Although some of the particular examples were not the type of examples I deal with, the reasons they were chosen make perfect sense. Data mining owes much of its popularity to people attempting to find churners, etc. But there are plenty. Ron Kohavi said A book from practitioners. Many books have been written on the algorithms used for data mining (e.g., machine learning, statistics). This is not yet another one.This book is geared at people who want to derive insight and take action in a business setting. It is now well known that the algorithmic step is only a small part of the iterative knowledge discovery process, yet few books enlighten the users with the issues involved.This book has a small section on the algorithms, but concentrates on the often-overlooked PROCESS of data mining (sometimes called knowledge discovery) and the problems ass. A master piece E. VAIOPOULOS Although aged the book remains a precious guide for business and CRM people. It argues that data mining is a discipline that must be mastered by concentrating in how to approach analytics than how to use tools. Specifically it stresses the importance of:- the iterative nature of data mining activities (and project life cycle)- the active involvement of business people- the business objectives and needs- the preparation and split of the model set (mining view)- the evaluation of produced models and patterns- the business interpretation of data mining results- the power