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Cluster Analysis for Researchers Paperback – March 30, 2004

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Product Details

  • Paperback: 340 pages
  • Publisher: Lulu.com (March 30, 2004)
  • Language: English
  • ISBN-10: 1411606175
  • ISBN-13: 978-1411606173
  • Product Dimensions: 6 x 0.8 x 9 inches
  • Shipping Weight: 1.2 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (6 customer reviews)
  • Amazon Best Sellers Rank: #1,166,454 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

24 of 25 people found the following review helpful By Thomas W. Powell on September 27, 2004
Format: Paperback
I first ran across Romesburg's "Cluster Analysis for Researchers" when I was designing my dissertation. Unlike most books on multivariate statistics, this volumee spoke to me in a language I could understand. The author assumes no previous knowledge of the topic, and does a fine job of providing the reader with a framework. Examples are clear and well chosen.

For years, I looked for a reasonably priced copy of this book for my personal library. I'm thrilled that it is in print again. This paperback edition is published by [...] and is faithful to the original version. It is highly recommended as an introduction to cluster analysis.
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4 of 4 people found the following review helpful By Maggiexyz on January 27, 2008
Format: Paperback
I originally borrowed this book from a library rather than bought it because I was worried that the book was published before the PC age and wouldn't cover modern clustering methods. That concern is legitimate--the book didn't even mention K-means. But the author did a great job explaining the logic behind cluster analyses. There are many subjective choices to make in performing a cluster analysis, with or without the aid of modern computing powers. The author highlighted the aspects of consideration when facing such choices, for example, why one would want to standardize the data matrix, what properties the (myriad) similarity coefficients have. The explanations are clear and to the point. I feel that I now know enough about what I need/what a cluster analysis can do, that I can decide with reasonable confidence which clustering methods out there may be appropriate for my analyses. I'm now buying the book for future reference.
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4 of 6 people found the following review helpful By N. Jespersen on May 10, 2008
Format: Paperback
I dont like this book. I find its structure confusing and its layout very unattractive (no margins!). I have used it with some similar book, and every time a have tried to look for some topic in this book i found it failed (or at least did at bad job).

I recomment B.S Everitt, Cluster Analysis for an overview, and Gan, Ma And Wu: Data clustering, theory, algoritms and applications for at very comprehensive how-to guide for the many different methods.
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