Data Mining Techniques : For Marketing, Sales, and Customer Support
Author: Michael J. A. Berry, Gordon Linoff
List Price: $60.00
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ISBN: 0471179809
Publisher: John Wiley & Sons (27 May, 1997)
Sales Rank: 49,252
Average Customer Rating: 3.37 out of 5
Customer Reviews
Rating: 4 out of 5
Good Introduction book, not limited to Marketing
The authors explain in a detailed way the most popular Data Mining techniques. The topics about Neuronal Networks, Decision Trees, Market-Basket Analysis and Memory-Based Reasoning are excellent. I think the topic Genetic Algorithms could be a bit more developed, but for the beginner is a good first overview. I have missed a topic about fuzzy logic. Given that the 90% of Data Mining projects are based on Marketing (1:1), the book is absolutely suitable for starting with these concepts, although I feel the book can be used in any other field (Just-In-Time Inventory, Demand Forecasting, Supply Value Chain, etc.)
In my opinion, it was very useful for my work and I considered it as a reference book.
Rating: 3 out of 5
Depends what you want this book for
This book gives an overview of what data mining is and the tools available to perform it; Market Basket Analysis, Memory Based Reasoning, Automatic Cluster Detection, Link Analysis, Decision Trees, Artificial Neural Networks. Genetic Algorithms are also included, which, while not a data mining tool, are being used to train neural nets.In each case the authors describe the principles behind the tool, its strengths and weaknesses and applications were it is applicable. The authors give tips on what data preparation is required for the tool, both in terms of data "massaging", (which is required for neural nets) and indicate were it is important to select training sets that have approximately equal proportions of "good" & "bad" outcomes, in order for the tool to predict correctly.
The descriptions include simple examples of the tool to give an overview of how the tool works. But as the title indicates, this book is for users who are considering using data mining tools. It does not describe how to use particular applications, neither does it include code examples (pseudo or actual) if you are interesting in developing your own tools.
The book is easy to read and includes many examples from their experience of data mining in the real world.
Rating: 1 out of 5
Too many words and little content
This book is very difficult to read. The authors say very little in hundreds of pages. I was looking for more content. The data mining techniques are explained in detail, but they are very difficult to understand. Perhaps this could also be because I am new to data mining. This is definitely not a book for someone looking for a quick introduction to data mining. Similar Products
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