Core Data Analysis: Summarization, Correlation, and Visualization (Record no. 184769)

MARC details
000 -LEADER
fixed length control field 03926nam a22005535i 4500
001 - CONTROL NUMBER
control field 978-3-030-00271-8
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423130056.0
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 190415s2019 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783030002718
-- 978-3-030-00271-8
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-030-00271-8
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q336
072 #7 - SUBJECT CATEGORY CODE
Subject category code UN
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM021000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UN
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.7
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Mirkin, Boris.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Core Data Analysis: Summarization, Correlation, and Visualization
Medium [electronic resource] /
Statement of responsibility, etc by Boris Mirkin.
250 ## - EDITION STATEMENT
Edition statement 2nd ed. 2019.
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2019.
300 ## - PHYSICAL DESCRIPTION
Extent XV, 524 p. 187 illus., 80 illus. in color.
Other physical details online resource.
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-- online resource
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347 ## -
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490 1# - SERIES STATEMENT
Series statement Undergraduate Topics in Computer Science,
International Standard Serial Number 2197-1781
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Topics in Data Analysis Substance -- Quantitative Summarization -- Learning Correlations -- Core Partitioning: K-Means and Similarity Clustering -- Divisive and Separate Cluster Structures -- Appendix. Basic Math and Code -- Index.
520 ## - SUMMARY, ETC.
Summary, etc This text examines the goals of data analysis with respect to enhancing knowledge, and identifies data summarization and correlation analysis as the core issues. Data summarization, both quantitative and categorical, is treated within the encoder-decoder paradigm bringing forward a number of mathematically supported insights into the methods and relations between them. Two Chapters describe methods for categorical summarization: partitioning, divisive clustering and separate cluster finding and another explain the methods for quantitative summarization, Principal Component Analysis and PageRank. Features: · An in-depth presentation of K-means partitioning including a corresponding Pythagorean decomposition of the data scatter. · Advice regarding such issues as clustering of categorical and mixed scale data, similarity and network data, interpretation aids, anomalous clusters, the number of clusters, etc. · Thorough attention to data-driven modelling including a number of mathematically stated relations between statistical and geometrical concepts including those between goodness-of-fit criteria for decision trees and data standardization, similarity and consensus clustering, modularity clustering and uniform partitioning. New edition highlights: · Inclusion of ranking issues such as Google PageRank, linear stratification and tied rankings median, consensus clustering, semi-average clustering, one-cluster clustering · Restructured to make the logics more straightforward and sections self-contained Core Data Analysis: Summarization, Correlation and Visualization is aimed at those who are eager to participate in developing the field as well as appealing to novices and practitioners. .
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data protection.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science
General subdivision Mathematics.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Science.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data and Information Security.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Mining and Knowledge Discovery.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematical Applications in Computer Science.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783030002701
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783030002725
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Undergraduate Topics in Computer Science,
-- 2197-1781
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-030-00271-8">https://doi.org/10.1007/978-3-030-00271-8</a>
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks-CSE-Springer

No items available.

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