Data Mining: Concepts, Models and Techniques

Front Cover
Springer Science & Business Media, Mar 10, 2011 - Technology & Engineering - 360 pages

The knowledge discovery process is as old as Homo sapiens. Until some time ago this process was solely based on the ‘natural personal' computer provided by Mother Nature. Fortunately, in recent decades the problem has begun to be solved based on the development of the Data mining technology, aided by the huge computational power of the 'artificial' computers. Digging intelligently in different large databases, data mining aims to extract implicit, previously unknown and potentially useful information from data, since “knowledge is power”. The goal of this book is to provide, in a friendly way, both theoretical concepts and, especially, practical techniques of this exciting field, ready to be applied in real-world situations. Accordingly, it is meant for all those who wish to learn how to explore and analysis of large quantities of data in order to discover the hidden nugget of information.

 

Selected pages

Contents

Introduction to Data Mining
1
The DataMine
45
Exploratory Data Analysis
57
Classification and Decision Trees
158
Data Mining Techniques and Models
185
Classification Performance Evaluation
318
References
331
Index
353
Copyright

Other editions - View all

Data Mining: Concepts, Models and Techniques
Florin Gorunescu
No preview available - 2011
Data Mining: Concepts, Models and Techniques
Florin Gorunescu
No preview available - 2013

Common terms and phrases

accuracy algorithm analysis applications approach attributes building called choose chosen classification clustering components computing concerning conditional consider consists context continuous correlation corresponding data mining database dataset decision decision tree defined dependent disease distance distribution error estimate example field function genetic given identify illustrate important individuals input instance interval knowledge known learning linear machine mean measure mention method mutation nature neural networks neuron node Note objects observations obtained operators optimal output parameters parents particular patients pattern perceptron performance population positive possible prediction present principle probability problem random refers regarding regression Remark representation represents rules sample selection separation similarity single situation solve space specific splitting starting statistical step Table Taxable income techniques term testing tion usually values variables vector weight

Bibliographic information

TitleData Mining: Concepts, Models and Techniques
Volume 12 of Intelligent Systems Reference Library
AuthorFlorin Gorunescu
Editionillustrated
PublisherSpringer Science & Business Media, 2011
ISBN3642197213, 9783642197215
Length360 pages
Subjects ›  › 

Computers / Artificial Intelligence / General
Technology & Engineering / Engineering (General)
Technology & Engineering / General
  
Export CitationBiBTeX EndNote RefMan