Language:
English
繁體中文
Help
Login
Back
to Search results for
[ subject:"Statistical data." ]
Switch To:
Labeled
|
MARC Mode
|
ISBD
Seriation in Combinatorial and Statistical Data Analysis
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Seriation in Combinatorial and Statistical Data Analysis/ by Israël César Lerman, Henri Leredde.
Author:
Lerman, Israël César.
other author:
Leredde, Henri.
Description:
XIV, 277 p. 114 illus., 6 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Machine Learning. -
Online resource:
https://doi.org/10.1007/978-3-030-92694-6
ISBN:
9783030926946
Seriation in Combinatorial and Statistical Data Analysis
Lerman, Israël César.
Seriation in Combinatorial and Statistical Data Analysis
[electronic resource] /by Israël César Lerman, Henri Leredde. - 1st ed. 2022. - XIV, 277 p. 114 illus., 6 illus. in color.online resource. - Advanced Information and Knowledge Processing,2197-8441. - Advanced Information and Knowledge Processing,.
Preface -- Acknowledgements -- General Introduction. Methods and History -- Seriation from Proximity Variance Analysis -- Main Approachs in Seriation. The Attraction Pole Case -- Comparing Geometrical and Ordinal Seriation Methods in Formal and Real Cases -- A New Family of Combinatorial Algorithms in Seriation -- Clustering Methods from Proximity Variance Analysis -- Conclusion and Developments.
This monograph offers an original broad and very diverse exploration of the seriation domain in data analysis, together with building a specific relation to clustering. Relative to a data table crossing a set of objects and a set of descriptive attributes, the search for orders which correspond respectively to these two sets is formalized mathematically and statistically. State-of-the-art methods are created and compared with classical methods and a thorough understanding of the mutual relationships between these methods is clearly expressed. The authors distinguish two families of methods: Geometric representation methods Algorithmic and Combinatorial methods Original and accurate methods are provided in the framework for both families. Their basis and comparison is made on both theoretical and experimental levels. The experimental analysis is very varied and very comprehensive. Seriation in Combinatorial and Statistical Data Analysis has a unique character in the literature falling within the fields of Data Analysis, Data Mining and Knowledge Discovery. It will be a valuable resource for students and researchers in the latter fields.
ISBN: 9783030926946
Standard No.: 10.1007/978-3-030-92694-6doiSubjects--Topical Terms:
1137723
Machine Learning.
LC Class. No.: QA76.9.D343
Dewey Class. No.: 006.312
Seriation in Combinatorial and Statistical Data Analysis
LDR
:03053nam a22004335i 4500
001
1089494
003
DE-He213
005
20220304031011.0
007
cr nn 008mamaa
008
221228s2022 sz | s |||| 0|eng d
020
$a
9783030926946
$9
978-3-030-92694-6
024
7
$a
10.1007/978-3-030-92694-6
$2
doi
035
$a
978-3-030-92694-6
050
4
$a
QA76.9.D343
072
7
$a
UNF
$2
bicssc
072
7
$a
UYQE
$2
bicssc
072
7
$a
COM021030
$2
bisacsh
072
7
$a
UNF
$2
thema
072
7
$a
UYQE
$2
thema
082
0 4
$a
006.312
$2
23
100
1
$a
Lerman, Israël César.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1271610
245
1 0
$a
Seriation in Combinatorial and Statistical Data Analysis
$h
[electronic resource] /
$c
by Israël César Lerman, Henri Leredde.
250
$a
1st ed. 2022.
264
1
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2022.
300
$a
XIV, 277 p. 114 illus., 6 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
490
1
$a
Advanced Information and Knowledge Processing,
$x
2197-8441
505
0
$a
Preface -- Acknowledgements -- General Introduction. Methods and History -- Seriation from Proximity Variance Analysis -- Main Approachs in Seriation. The Attraction Pole Case -- Comparing Geometrical and Ordinal Seriation Methods in Formal and Real Cases -- A New Family of Combinatorial Algorithms in Seriation -- Clustering Methods from Proximity Variance Analysis -- Conclusion and Developments.
520
$a
This monograph offers an original broad and very diverse exploration of the seriation domain in data analysis, together with building a specific relation to clustering. Relative to a data table crossing a set of objects and a set of descriptive attributes, the search for orders which correspond respectively to these two sets is formalized mathematically and statistically. State-of-the-art methods are created and compared with classical methods and a thorough understanding of the mutual relationships between these methods is clearly expressed. The authors distinguish two families of methods: Geometric representation methods Algorithmic and Combinatorial methods Original and accurate methods are provided in the framework for both families. Their basis and comparison is made on both theoretical and experimental levels. The experimental analysis is very varied and very comprehensive. Seriation in Combinatorial and Statistical Data Analysis has a unique character in the literature falling within the fields of Data Analysis, Data Mining and Knowledge Discovery. It will be a valuable resource for students and researchers in the latter fields.
650
2 4
$a
Machine Learning.
$3
1137723
650
2 4
$a
Mathematics of Computing.
$3
669457
650
1 4
$a
Data Mining and Knowledge Discovery.
$3
677765
650
0
$a
Machine learning.
$3
561253
650
0
$a
Computer science—Mathematics.
$3
1253519
650
0
$a
Data mining.
$3
528622
700
1
$a
Leredde, Henri.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1396769
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783030926939
776
0 8
$i
Printed edition:
$z
9783030926953
776
0 8
$i
Printed edition:
$z
9783030926960
830
0
$a
Advanced Information and Knowledge Processing,
$x
1610-3947
$3
1254273
856
4 0
$u
https://doi.org/10.1007/978-3-030-92694-6
912
$a
ZDB-2-SCS
912
$a
ZDB-2-SXCS
950
$a
Computer Science (SpringerNature-11645)
950
$a
Computer Science (R0) (SpringerNature-43710)
based on 0 review(s)
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login