Principles Of Data Mining

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Principles of Data Mining

Max Bramer
Principles of Data Mining Book PDF

Author : Max Bramer
Publisher : Springer
Page : 526 pages
File Size : 42,9 Mb
Release : 2016-11-09
Category : Computers
ISBN : 9781447173076

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Principles of Data Mining by Max Bramer Pdf

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

David J. Hand,Heikki Mannila,Padhraic Smyth
Principles of Data Mining Book PDF

Author : David J. Hand,Heikki Mannila,Padhraic Smyth
Publisher : MIT Press
Page : 594 pages
File Size : 54,7 Mb
Release : 2001-08-17
Category : Computers
ISBN : 026208290X

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Principles of Data Mining by David J. Hand,Heikki Mannila,Padhraic Smyth Pdf

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

Max Bramer
Principles of Data Mining Book PDF

Author : Max Bramer
Publisher : Springer Science & Business Media
Page : 342 pages
File Size : 43,6 Mb
Release : 2007-03-06
Category : Computers
ISBN : 9781846287664

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Principles of Data Mining by Max Bramer Pdf

This book explains the principal techniques of data mining: for classification, generation of association rules and clustering. It is written for readers without a strong background in mathematics or statistics and focuses on detailed examples and explanations of the algorithms given. This will benefit readers of all levels, from those who use data mining via commercial packages, right through to academic researchers. The book aims to help the general reader develop the necessary understanding to use commercial data mining packages, and to enable advanced readers to understand or contribute to future technical advances. Includes exercises and glossary.

Principles and Theory for Data Mining and Machine Learning

Bertrand Clarke,Ernest Fokoue,Hao Helen Zhang
Principles and Theory for Data Mining and Machine Learning Book PDF

Author : Bertrand Clarke,Ernest Fokoue,Hao Helen Zhang
Publisher : Springer Science & Business Media
Page : 786 pages
File Size : 46,5 Mb
Release : 2009-07-21
Category : Computers
ISBN : 9780387981352

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Principles and Theory for Data Mining and Machine Learning by Bertrand Clarke,Ernest Fokoue,Hao Helen Zhang Pdf

Extensive treatment of the most up-to-date topics Provides the theory and concepts behind popular and emerging methods Range of topics drawn from Statistics, Computer Science, and Electrical Engineering

Data Mining and Data Warehousing

Parteek Bhatia
Data Mining and Data Warehousing Book PDF

Author : Parteek Bhatia
Publisher : Cambridge University Press
Page : 513 pages
File Size : 53,8 Mb
Release : 2019-06-27
Category : Computers
ISBN : 9781108727747

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Data Mining and Data Warehousing by Parteek Bhatia Pdf

Provides a comprehensive textbook covering theory and practical examples for a course on data mining and data warehousing.

Principles of Data Mining and Knowledge Discovery

Jan Zytkow,Jan Rauch
Principles of Data Mining and Knowledge Discovery Book PDF

Author : Jan Zytkow,Jan Rauch
Publisher : Springer Science & Business Media
Page : 608 pages
File Size : 50,7 Mb
Release : 1999-09-01
Category : Computers
ISBN : 9783540664901

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Principles of Data Mining and Knowledge Discovery by Jan Zytkow,Jan Rauch Pdf

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 for Co-location Patterns

Guoqing Zhou
Data Mining for Co location Patterns Book PDF

Author : Guoqing Zhou
Publisher : CRC Press
Page : 229 pages
File Size : 41,7 Mb
Release : 2022-01-26
Category : Technology & Engineering
ISBN : 9781000533439

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Data Mining for Co-location Patterns by Guoqing Zhou Pdf

Co-location pattern mining detects sets of features frequently located in close proximity to each other. This book focuses on data mining for co-location pattern, a valid method for identifying patterns from all types of data and applying them in business intelligence and analytics. It explains the fundamentals of co-location pattern mining, co-location decision tree, and maximal instance co-location pattern mining along with an in-depth overview of data mining, machine learning, and statistics. This arrangement of chapters helps readers understand the methods of co-location pattern mining step-by-step and their applications in pavement management, image classification, geospatial buffer analysis, etc.

Machine Learning and Data Mining

Igor Kononenko,Matjaz Kukar
Machine Learning and Data Mining Book PDF

Author : Igor Kononenko,Matjaz Kukar
Publisher : Horwood Publishing
Page : 484 pages
File Size : 50,6 Mb
Release : 2007-04-30
Category : Computers
ISBN : 1904275214

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Machine Learning and Data Mining by Igor Kononenko,Matjaz Kukar Pdf

Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. Written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining, this text is suitable foradvanced undergraduates, postgraduates and tutors in a wide area of computer science and technology, as well as researchers looking to adapt various algorithms for particular data mining tasks. A valuable addition to libraries and bookshelves of the many companies who are using the principles of data mining to effectively deliver solid business and industry solutions.

Data Mining: Concepts and Techniques

Jiawei Han,Micheline Kamber,Jian Pei
Data Mining Concepts and Techniques Book PDF

Author : Jiawei Han,Micheline Kamber,Jian Pei
Publisher : Elsevier
Page : 740 pages
File Size : 47,5 Mb
Release : 2011-06-09
Category : Computers
ISBN : 9780123814807

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Data Mining: Concepts and Techniques by Jiawei Han,Micheline Kamber,Jian Pei Pdf

Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

Practical Applications of Data Mining

Sang Suh
Practical Applications of Data Mining Book PDF

Author : Sang Suh
Publisher : Jones & Bartlett Publishers
Page : 436 pages
File Size : 53,9 Mb
Release : 2012
Category : Computers
ISBN : 9780763785871

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Practical Applications of Data Mining by Sang Suh Pdf

Introduction to data mining -- Association rules -- Classification learning -- Statistics for data mining -- Rough sets and bayes theories -- Neural networks -- Clustering -- Fuzzy information retrieval.

Data Mining

Harold L. Capri
Data Mining Book PDF

Author : Harold L. Capri
Publisher : Nova Science Publishers
Page : 0 pages
File Size : 41,7 Mb
Release : 2014
Category : Data mining
ISBN : 1634637380

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Data Mining by Harold L. Capri Pdf

Data mining is an area of research where appropriate methodological research and technical means are experienced to produce useful knowledge from different types of data. Data mining techniques use a broad family of computationally intensive methods that include decision trees, neural networks, rule induction, machine learning and graphic visualisation. This book discusses the principles, applications and emerging challenges of data mining.

Data Mining for Scientific and Engineering Applications

R.L. Grossman,C. Kamath,P. Kegelmeyer,V. Kumar,R. Namburu
Data Mining for Scientific and Engineering Applications Book PDF

Author : R.L. Grossman,C. Kamath,P. Kegelmeyer,V. Kumar,R. Namburu
Publisher : Springer Science & Business Media
Page : 608 pages
File Size : 41,8 Mb
Release : 2013-12-01
Category : Computers
ISBN : 9781461517337

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Data Mining for Scientific and Engineering Applications by R.L. Grossman,C. Kamath,P. Kegelmeyer,V. Kumar,R. Namburu Pdf

Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.

Data Mining and Knowledge Discovery with Evolutionary Algorithms

Alex A. Freitas
Data Mining and Knowledge Discovery with Evolutionary Algorithms Book PDF

Author : Alex A. Freitas
Publisher : Springer Science & Business Media
Page : 272 pages
File Size : 41,6 Mb
Release : 2013-11-11
Category : Computers
ISBN : 9783662049235

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Data Mining and Knowledge Discovery with Evolutionary Algorithms by Alex A. Freitas Pdf

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

Introduction to Data Mining and its Applications

S. Sumathi,S.N. Sivanandam
Introduction to Data Mining and its Applications Book PDF

Author : S. Sumathi,S.N. Sivanandam
Publisher : Springer
Page : 828 pages
File Size : 46,6 Mb
Release : 2006-10-12
Category : Computers
ISBN : 9783540343516

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Introduction to Data Mining and its Applications by S. Sumathi,S.N. Sivanandam Pdf

This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in database systems, and presents a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, neural networks, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization.

Data Mining

Mehmed Kantardzic
Data Mining Book PDF

Author : Mehmed Kantardzic
Publisher : John Wiley & Sons
Page : 672 pages
File Size : 42,7 Mb
Release : 2019-11-12
Category : Computers
ISBN : 9781119516040

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Data Mining by Mehmed Kantardzic Pdf

Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization. Advances in deep learning technology have opened an entire new spectrum of applications. The author—a noted expert on the topic—explains the basic concepts, models, and methodologies that have been developed in recent years. This new edition introduces and expands on many topics, as well as providing revised sections on software tools and data mining applications. Additional changes include an updated list of references for further study, and an extended list of problems and questions that relate to each chapter.This third edition presents new and expanded information that: • Explores big data and cloud computing • Examines deep learning • Includes information on convolutional neural networks (CNN) • Offers reinforcement learning • Contains semi-supervised learning and S3VM • Reviews model evaluation for unbalanced data Written for graduate students in computer science, computer engineers, and computer information systems professionals, the updated third edition of Data Mining continues to provide an essential guide to the basic principles of the technology and the most recent developments in the field.