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Data Classification and Incremental Clustering in Data Mining and Machine Learning (Record no. 200458520)

MARC details
000 -LEADER
fixed length control field	04178nam a22005655i 4500
003 - CONTROL NUMBER IDENTIFIER
control field	TR-AnTOB
005 - DATE AND TIME OF LATEST TRANSACTION
control field	20231116084054.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field	cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field	220510s2022 sz \| s \|\|\|\| 0\|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number	9783030930882
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code	10.1007/978-3-030-93088-2
Source of number or code	doi
040 ## - CATALOGING SOURCE
Original cataloging agency	TR-AnTOB
Language of cataloging	eng
Description conventions	rda
Transcribing agency	TR-AnTOB
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title	İngilizce
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number	QA76.9.D343
072 #7 - SUBJECT CATEGORY CODE
Subject category code	TJK
Source	bicssc

Subject category code	TEC041000
Source	bisacsh

Subject category code	TJK
Source	thema
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR)	QA76.9.D343EBK
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name	Chakraborty, Sanjay.
Relator term	author.
Relator code	aut
--	http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title	Data Classification and Incremental Clustering in Data Mining and Machine Learning
Medium	[electronic resource] /
Statement of responsibility, etc.	by Sanjay Chakraborty, Sk Hafizul Islam, Debabrata Samanta.
250 ## - EDITION STATEMENT
Edition statement	1st ed. 2022.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture	Cham :
Name of producer, publisher, distributor, manufacturer	Springer International Publishing :
--	Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice	2022.
300 ## - PHYSICAL DESCRIPTION
Extent	1 online resource
336 ## - CONTENT TYPE
Content type term	text
Content type code	txt
Source	rdacontent
337 ## - MEDIA TYPE
Media type term	computer
Media type code	c
Source	rdamedia
338 ## - CARRIER TYPE
Carrier type term	online resource
Carrier type code	cr
Source	rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type	text file
Encoding format	PDF
Source	rda
490 1# - SERIES STATEMENT
Series statement	EAI/Springer Innovations in Communication and Computing,
International Standard Serial Number	2522-8609
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note	Introduction to Data Mining & Knowledge Discovery -- A Brief Concept on Machine Learning -- Supervised Learning based Data Classification and Incremental Clustering -- Data Classification and Incremental Clustering using Unsupervised Learning -- Research Intention towards Incremental Clustering -- Applications and Trends in Data Mining & Machine Learning -- Feature subset selection techniques with Machine Learning -- Data Mining Based variant subsets features.
520 ## - SUMMARY, ETC.
Summary, etc.	This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naïve Bayes, Decision tree, Random forest, Support vector machine etc,) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques. Provides a comprehensive review of various data mining techniques and architecture, primarily focusing on supervised and unsupervised learning Presents hands-on coding examples using three popular coding platforms: R, Python, and Java Includes case-studies, examples, practice problems, questions, and solutions for students and professionals, focusing on machine learning and data science.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element	Telecommunication.

Topical term or geographic name entry element	Computational intelligence.

Topical term or geographic name entry element	Computer vision.

Topical term or geographic name entry element	Data mining.

Topical term or geographic name entry element	Communications Engineering, Networks.

Topical term or geographic name entry element	Computational Intelligence.

Topical term or geographic name entry element	Computer Vision.

Topical term or geographic name entry element	Data Mining and Knowledge Discovery.
653 #0 - INDEX TERM--UNCONTROLLED
Uncontrolled term	Machine learning
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name	Islam, Sk Hafizul.
Relator term	author.
Relator code	aut
--	http://id.loc.gov/vocabulary/relators/aut

Personal name	Samanta, Debabrata.
Relator term	author.
Relator code	aut
--	http://id.loc.gov/vocabulary/relators/aut
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element	SpringerLink (Online service)
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title	EAI/Springer Innovations in Communication and Computing,
International Standard Serial Number	2522-8609
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier	<a href="https://doi.org/10.1007/978-3-030-93088-2">https://doi.org/10.1007/978-3-030-93088-2</a>
Materials specified	Springer eBooks
Public note	Online access link to the resource
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme	Library of Congress Classification
Koha item type	E-Book

Holdings
Withdrawn status	Lost status	Source of classification or shelving scheme	Not for loan	Collection code	Home library	Current library	Date acquired	Source of acquisition	Coded location qualifier	Inventory number	Total Checkouts	Full call number	Barcode	Date last seen	Copy number	Date shelved	Koha item type	Public note
		Library of Congress Classification	Geçerli değil-e-Kitap / Not applicable-e-Book	E-Kitap Koleksiyonu	Merkez Kütüphane	Merkez Kütüphane	11/10/2023	Satın Alma / Purchase		BİL/YAP		QA76.9.D343EBK	EBK02917	16/11/2023	1	16/11/2023	E-Book