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Principles of Data Mining

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Release : 2016-11-09
Genre : Computers
Kind : eBook
Book Rating : 074/5 ( reviews)

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Book Synopsis Principles of Data Mining by : Max Bramer

Download or read book Principles of Data Mining written by Max Bramer. This book was released on 2016-11-09. Available in PDF, EPUB and Kindle. Book excerpt: This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering. Each topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked examples. The book is written for readers without a strong background in mathematics or statistics and any formulae used are explained in detail. It can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. As an aid to self study, this book aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field. Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included. This expanded third edition includes detailed descriptions of algorithms for classifying streaming data, both stationary data, where the underlying model is fixed, and data that is time-dependent, where the underlying model changes from time to time - a phenomenon known as concept drift.

Principles of Data Mining and Knowledge Discovery

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Release : 1999-09-01
Genre : Computers
Kind : eBook
Book Rating : 904/5 ( reviews)

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Book Synopsis Principles of Data Mining and Knowledge Discovery by : Jan Zytkow

Download or read book Principles of Data Mining and Knowledge Discovery written by Jan Zytkow. This book was released on 1999-09-01. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD'99, held in Prague, Czech Republic in September 1999. The 28 revised full papers and 48 poster presentations were carefully reviewed and selected from 106 full papers submitted. The papers are organized in topical sections on time series, applications, taxonomies and partitions, logic methods, distributed and multirelational databases, text mining and feature selection, rules and induction, and interesting and unusual issues.

Principles of Data Mining

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Author :
Release : 2001-08-17
Genre : Computers
Kind : eBook
Book Rating : 907/5 ( reviews)

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Book Synopsis Principles of Data Mining by : David J. Hand

Download or read book Principles of Data Mining written by David J. Hand. This book was released on 2001-08-17. Available in PDF, EPUB and Kindle. Book excerpt: The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.

Principles of Data Mining and Knowledge Discovery

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Author :
Release : 2004-06-08
Genre : Computers
Kind : eBook
Book Rating : 474/5 ( reviews)

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Book Synopsis Principles of Data Mining and Knowledge Discovery by : Jan Zytkow

Download or read book Principles of Data Mining and Knowledge Discovery written by Jan Zytkow. This book was released on 2004-06-08. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD'99, held in Prague, Czech Republic in September 1999. The 28 revised full papers and 48 poster presentations were carefully reviewed and selected from 106 full papers submitted. The papers are organized in topical sections on time series, applications, taxonomies and partitions, logic methods, distributed and multirelational databases, text mining and feature selection, rules and induction, and interesting and unusual issues.

Data Mining and Knowledge Discovery with Evolutionary Algorithms

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Release : 2013-11-11
Genre : Computers
Kind : eBook
Book Rating : 236/5 ( reviews)

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Book Synopsis Data Mining and Knowledge Discovery with Evolutionary Algorithms by : Alex A. Freitas

Download or read book Data Mining and Knowledge Discovery with Evolutionary Algorithms written by Alex A. Freitas. This book was released on 2013-11-11. Available in PDF, EPUB and Kindle. Book excerpt: This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics

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