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EDIT: After using this book for class, I will repeat, AVOID THIS BOOK and especially avoid XL Miner. I did like the chapter on Naive Bayes. The rest is written poorly. The worst part though is the use of Analytic Solver XLminor Excel add-on. Do not work as expected, support info is lousy, "live chat" is actually an email you have to wait for a reply. The book requires you to use XL minor for the problems at the end of chapters, but it seems like there is always missing info, sheets, and instructions in the provided excel files. It will literally tell you to refer to sheets that do not exist in the workbook. It will then tell you to do a partition on the data to only find out your student license limits you from doing as instructed. But you can upgrade for $2000!! Stay away from this book, but even more importantly, STAY AWAY FROM ANALYTIC SOLVERS for Excel.
Book is not written very clearly and some sentences make an absolute mess of syntax and require being re-read multiple times. It definitely assumes you have a firm grasp of statistical concepts and vocabulary (they will use a lot of interchangeable synonyms throughout). It's based on using XLminer which is just as much of a headache and a pain. Look in Excel add-ons for XLminer and read those reviews to get a better picture. The authors do not explain how to use XLminer very well and there are many issues when using on Excel 365 online. I'll be removing XLminer as soon as my classes are done. This book was required for a course, but there is better material out there.
Excellent book to whom uses XLMiner software. The author explains in a easy manner what are the main features employed by the Industry in Data Mining using XLMiner as add in in Excel spreadsheet. Highly recommended book to whom wants to use XLMiner. However I would recommend the author to include more examples in the use of the add-in.
I would avoid any class that requires this textbook. As someone who read this book as a part of an elective for my MPAcc program, I can safely say that this book is not intended for anyone that doesn’t already have a solid foundation of data mining.
Covers more stuff than a similar book called "Data Mining for Business Intelligence ...". Slightly more technical, but still focuses on qualitative traits of common DM techniques. Statistics and implementation details are not the emphasis of the book.
It's easy enough to skim through this book and use it as a guide to the stats functions of the software, but if you want to take a deeper dive into the subject matter, the information is there for you as well. There is really no "fluff" in this book, and I'll be keeping it as a reference.
I used the book as a textbook for my class "Data Mining for Business" and I am very satisfied. The examples are rich, concepts are explained in a non-technical way and are easy to follow. For the class, I used R instead of XLMiner without any problems for the students and teaching process.
It's okay. You have to realize its written to support commercial software. It was required reading for a class, and I don't think I could have followed the concepts without an instructors help. Its written in such a way you would think the author(s) were really trying to impress themselves with their vocabulary, and how complex they could make trivial tasks seem.