MARC details
| 000 -LEADER |
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| fixed length control field |
03034nam a2200385 i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
CR9781139025805 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
UkCbUP |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20240807185053.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
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| fixed length control field |
m|||||o||d|||||||| |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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| fixed length control field |
cr|||||||||||| |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
110218s2014||||enk o ||1 0|eng|d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781139025805 (ebook) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| Canceled/invalid ISBN |
9780521887939 (hardback) |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
UkCbUP |
| Language of cataloging |
eng |
| Description conventions |
rda |
| Transcribing agency |
UkCbUP |
| 050 00 - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
QA278 |
| Item number |
.K5935 2014 |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
519.5/35 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Koch, Inge, |
| Dates associated with a name |
1952- |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
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| Title |
Analysis of multivariate and high-dimensional data / |
| Statement of responsibility, etc. |
Inge Koch, University of Adelaide, Australia. |
| 246 3# - VARYING FORM OF TITLE |
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| Title proper/short title |
Analysis of Multivariate & High-Dimensional Data |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
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| Place of production, publication, distribution, manufacture |
Cambridge : |
| Name of producer, publisher, distributor, manufacturer |
Cambridge University Press, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2014. |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
1 online resource (xxv, 504 pages) : |
| Other physical details |
digital, PDF file(s). |
| 336 ## - CONTENT TYPE |
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| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
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| Media type term |
computer |
| Media type code |
c |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
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| Carrier type term |
online resource |
| Carrier type code |
cr |
| Source |
rdacarrier |
| 490 1# - SERIES STATEMENT |
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| Series statement |
Cambridge series on statistical and probabilistic mathematics ; |
| Volume/sequential designation |
32 |
| 500 ## - GENERAL NOTE |
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| General note |
Title from publisher's bibliographic system (viewed on 05 Oct 2015). |
| 505 8# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Machine generated contents note: Part I. Classical Methods: 1. Multidimensional data; 2. Principal component analysis; 3. Canonical correlation analysis; 4. Discriminant analysis; Part II. Factors and Groupings: 5. Norms, proximities, features, and dualities; 6. Cluster analysis; 7. Factor analysis; 8. Multidimensional scaling; Part III. Non-Gaussian Analysis: 9. Towards non-Gaussianity; 10. Independent component analysis; 11. Projection pursuit; 12. Kernel and more independent component methods; 13. Feature selection and principal component analysis revisited; Index. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guaranteed 'safe operating zone' for the methods and allow you to assess whether data is in the zone, or near enough. Extensive examples showcase the strengths and limitations of different methods with small classical data, data from medicine, biology, marketing and finance, high-dimensional data from bioinformatics, functional data from proteomics, and simulated data. High-dimension low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code, and problem sets complete the package. Suitable for master's/graduate students in statistics and researchers in data-rich disciplines. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Multivariate analysis. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Big data. |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
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| Relationship information |
Print version: |
| International Standard Book Number |
9780521887939 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Cambridge series on statistical and probabilistic mathematics ; |
| Volume/sequential designation |
32. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
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| Uniform Resource Identifier |
<a href="https://doi.org/10.1017/CBO9781139025805">https://doi.org/10.1017/CBO9781139025805</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
eBooks |
