Data Mining: Concepts, Models, Methods, and Algorithms
β Scribed by Mehmed Kantardzic
- Publisher
- Wiley-IEEE Press
- Year
- 2002
- Tongue
- English
- Leaves
- 360
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
A comprehensive introduction to the exploding field of data miningWe are surrounded by data, numerical and otherwise, which must be analyzed and processed to convert it into information that informs, instructs, answers, or otherwise aids understanding and decision-making. Due to the ever-increasing complexity and size of today's data sets, a new term, data mining, was created to describe the indirect, automatic data analysis techniques that utilize more complex and sophisticated tools than those which analysts used in the past to do mere data analysis.Data Mining: Concepts, Models, Methods, and Algorithms discusses data mining principles and then describes representative state-of-the-art methods and algorithms originating from different disciplines such as statistics, machine learning, neural networks, fuzzy logic, and evolutionary computation. Detailed algorithms are provided with necessary explanations and illustrative examples.This text offers guidance: how and when to use a particular software tool (with their companion data sets) from among the hundreds offered when faced with a data set to mine. This allows analysts to create and perform their own data mining experiments using their knowledge of the methodologies and techniques provided.This book emphasizes the selection of appropriate methodologies and data analysis software, as well as parameter tuning. These critically important, qualitative decisions can only be made with the deeper understanding of parameter meaning and its role in the technique that is offered here. Data mining is an exploding field and this book offers much-needed guidance to selecting among the numerous analysis programs that are available.
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This book reviews state-of-the-art methodologies and techniques for analyzing enormous quantities of raw data in high-dimensional data spaces, to extract new information for decision making. TheΒ goal of this book is toΒ provide a single introductory source, organized in a systematic way, in which we
<b>Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces</b><br /><br />The revised and updated third edition of<i>Data Mining</i>contains in one volume an introduction to a systematic approach to the analysis of large data
<b>Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces</b><br /><br />The revised and updated third edition of<i>Data Mining</i>contains in one volume an introduction to a systematic approach to the analysis of large data
This text offers guidance on how and when to use a particular software tool (with their companion data sets) from among the hundreds offered when faced with a data set to mine.