Discovering Knowledge in Data: An Introduction to Data Mining

by Daniel T. Larose, Chantal D. Larose

This is a new edition of a highly praised, successful reference on data mining, now more important than ever due to the growth of the field and wide range of applications. This edition features new chapters on multivariate statistical analysis, covering analysis of variance and chi-square procedures; cost-benefit analyses; and time-series data analysis. There is also extensive coverage of the R statistical programming language. Graduate and advanced undergraduate students of computer science and statistics, managers/CEOs/CFOs, marketing executives, market researchers and analysts, sales analysts, and medical professionals will want this comprehensive reference.

Genres: Software, Academic

336 pages, Hardcover

First published November 18, 2004

Reviews

[Gabri · Rating 3 out of 5]

Mandatory read for school, did not finish around 20%.

The chapters are easy to follow. The chapter on Data preprocessing was very valuable to me, explaining why it's so important and which (statistical) methods could be used.
Unfortunately the way the results were being obtained (old version of SPSS) were not so relevant for me since in this course I have to use Python. It does seem like a good book to learn how Data Mining algorithms work and how to interpret its results.

[Stancalău · Rating 4 out of 5]

Really got me interested in the domain of data mining. It is rather an old book and I would have liked some more hands-on examples in a more modern mining tool. Nevertheless, worth the read.