Data mining : (Record no. 73945)

000 -LEADER
fixed length control field 05878nam a2201285 i 4500
001 - CONTROL NUMBER
control field 5265979
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220712205703.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 100317t20152003njua ob 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9780470544341
-- electronic
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
-- print
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
-- electronic
082 04 - CLASSIFICATION NUMBER
Call Number 006.3/12
100 1# - AUTHOR NAME
Author Kantardzic, Mehmed,
245 10 - TITLE STATEMENT
Title Data mining :
Sub Title concepts, models, methods, and algorithms /
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 PDF (xii, 345 pages) :
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Preparing the Data -- Data Reduction -- Learning from Data -- Statistical Methods -- Cluster Analysis -- Decision Trees and Decision Rules -- Association Rules -- Artificial Neural Networks -- Genetic Algorithms -- Fuzzy Sets and Fuzzy Logic -- Visualization Methods -- Data-Mining Tools -- Data-Mining Applications.
520 ## - SUMMARY, ETC.
Summary, etc A comprehensive introduction to the exploding field of data mining We 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.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
Subject Data mining.
856 42 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5265979
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Hoboken, New Jersey :
-- Wiley-Interscience,
-- 2003.
264 #2 -
-- [Piscataqay, New Jersey] :
-- IEEE Xplore,
-- [2009]
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-- text
-- rdacontent
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-- electronic
-- isbdmedia
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-- online resource
-- rdacarrier
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-- Description based on PDF viewed 12/21/2015.
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-- Neurons
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-- Optical fiber cables
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-- Optimization
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-- Parameter estimation
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-- Partitioning algorithms
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-- Predictive models
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-- Rain
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-- Sections
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-- Servers
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-- Shape
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-- Statistical analysis
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-- System identification
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-- Telecommunications
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-- Temperature measurement
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-- Three dimensional displays
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-- Training
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-- Training data
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-- Visualization
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-- Accuracy
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-- Adaptive systems
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-- Algorithm design and analysis
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-- Analytical models
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-- Approximation algorithms
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-- Approximation methods
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-- Artificial neural networks
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-- Association rules
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-- Bibliographies
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-- Biographies
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-- Biological cells
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-- Business
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-- Cable TV
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-- Cities and towns
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-- Classification algorithms
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-- Classification tree analysis
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-- Clustering algorithms
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-- Communities
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-- Companies
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-- Complexity theory
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-- Computational modeling
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-- Data analysis
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-- Data mining
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-- Data models
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-- Data visualization
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-- Databases
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-- Dispersion
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-- Distributed databases
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-- Encoding
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-- Estimation
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-- Fault tolerance
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-- Fuzzy logic
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-- Fuzzy sets
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-- Gallium
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-- Generators
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-- Genetic algorithms
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-- Genetics
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-- Humans
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-- Hypercubes
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-- Image color analysis
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-- Indexes
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-- Industries
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-- Itemsets
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-- Learning
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-- Learning systems
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-- Loss measurement
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-- Machine learning
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-- Mathematical model
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-- Measurement uncertainty

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