Introduction to Data Mining

by Pang-Ning Tan, Michael Steinbach, Vipin Kumar

Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.

Genres: Computer Science, Nonfiction, Textbooks, Technology, Reference, Technical, Artificial Intelligence

792 pages, Hardcover

First published January 1, 2005

Reviews

[Erfan Abedi · Rating 2 out of 5]

Data Mining is boring as fuck.

[Xinyu Tan · Rating 4 out of 5]

As an introductory book, this book does a really good job. Explain well and easy to understand. I did not finish all the contents, probably 80 percent. May refer to it if later I encounter some algorithms I've seen in the book as a quick introduction. I also learned that in order to truly understand those algorithms, I should do some real-life project, apply those algorithms to some real data. Hmm, that's what I am trying to do.

[Turkan Ali]

i want read this book

[Deep Makwana]

good

[liyang · Rating 5 out of 5]

Do you guys have the ebook edition?

[Lê Thành · Rating 4 out of 5]

It's an introduction book, so you couldn't expect it to have fancy or state of the art algorithms in it. However, the content and examples were well written and explained. Traditional algorithms were also explained thoughtfully and comes with pseudo code. Some figures are really nice too, and I learnt that there was a type of figure named "Chernoff face", you should check it out:D. I was skimming this book, it's a good reference, and also a suitable book for data-mining newcomers.

[Michael Kareev · Rating 4 out of 5]

Extremely dry, need to have a good amount of knowledge already built before delving into this one

[Haseena Shaik · Rating 4 out of 5]

good

[Ariyasacca · Rating 3 out of 5]

An awkward book, not really an introduction. Too few examples for beginners and too little math for non-beginners.

[Brian · Rating 3 out of 5]

Decent as a reference book. Not something you'd ever want to just sit down and read if you're trying to learn the topic.

[Bushra GM · Rating 3 out of 5]

Ok , it was good , ,it was a very interesting subject to me in database field .
basics about data mining and how it differ from the relational database operations , warehouses , OLAP , data cube and how you visualize data in 3D, 4D ..how you classify data from human genes to chemical components , how you cluster based on shared properties or other ways .

if you into database design and modeling concepts then mapping to data mining techniques . So you need this book

+ the application you will work with when you will study this subject , is "Odiminer" it's a small file , will work will in your spreadsheets data to classify it , cluster it , find the noise and outliers among them.

[Pamela · Rating 3 out of 5]

This book is just fine as a quick guide to data mining. In my experience with it, reading entire chapters wasn't valuable. It's more of a good reference to figure out a concept in my more detail if your internet searching came up confusing.

[Alex · Rating 4 out of 5]

One of the less intimidating approaches - clear and straightforward.

[Mssab Obeado]

mas

[Anu]

excellent book

[Ali Irfan]

this a good book

[Yogesh Saharan]

7yy

[Prasanna Prasu · Rating 4 out of 5]

gud

[Sachin · Rating 5 out of 5]

Good book

[Joe Cole · Rating 5 out of 5]

The book was light on the math which was nice since it just got into the meat of the subject. Also, there's a nice appendix which does get in deeper into the mathematical foundation in case you need it.

[Nayeem Shaik]

good book

[Taufik Firmansah]

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