| bibtype |
J -
Journal Article
|
| ARLID |
0511450 |
| utime |
20240903203906.6 |
| mtime |
20191121235959.9 |
| SCOPUS |
85075353706 |
| WOS |
000504747200006 |
| DOI |
10.1007/s40300-019-00162-5 |
| title
(primary) (eng) |
Comparing clusterings using combination of the kappa statistic and entropy-based measure |
| specification |
| page_count |
17 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0348913 |
| ISSN |
0026-1424 |
| title
|
Metron |
| volume_id |
77 |
| volume |
3 (2019) |
| page_num |
253-270 |
| publisher |
|
|
| keyword |
Comparing clusterings |
| keyword |
Clusters agreement |
| keyword |
kappa max statistic |
| keyword |
Normalized mutual information |
| author
(primary) |
| ARLID |
cav_un_auth*0383037 |
| name1 |
Uglickich |
| name2 |
Evženie |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování signálů |
| full_dept (eng) |
Department of Signal Processing |
| department (cz) |
ZS |
| department (eng) |
ZS |
| full_dept |
Department of Signal Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101167 |
| name1 |
Nagy |
| name2 |
Ivan |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování signálů |
| full_dept |
Department of Signal Processing |
| department (cz) |
ZS |
| department |
ZS |
| full_dept |
Department of Signal Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0383038 |
| name1 |
Vlčková |
| name2 |
D. |
| country |
CZ |
|
| source |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0351997 |
| project_id |
8A17006 |
| agency |
GA MŠk |
| country |
CZ |
|
| abstract
(eng) |
The paper focuses on a problem of comparing clusterings with the same number of clusters obtained as a result of using different clustering algorithms. It proposes a method of the evaluation of the agreement of clusterings based on the combination of the Cohen's kappa statistic and the normalized mutual information. The main contributions of the proposed approach are: (i) the reliable use in practice in the case of a small fixed number of clusters, (ii) the suitability to comparing clusterings with a higher number of clusters in contrast with the original statistics, (iii) the independence on size of the data set and shape of clusters. Results of the experimental validation of the proposed statistic using both simulations and real data sets as well as the comparison with the theoretical counterparts are demonstrated. |
| result_subspec |
WOS |
| RIV |
BB |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10103 |
| reportyear |
2020 |
| num_of_auth |
3 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0302474 |
| confidential |
S |
| mrcbC86 |
3+4 Article Statistics Probability |
| mrcbC91 |
C |
| mrcbT16-s |
0.311 |
| mrcbT16-E |
Q4 |
| arlyear |
2019 |
| mrcbU14 |
85075353706 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000504747200006 WOS |
| mrcbU56 |
pdf |
| mrcbU63 |
cav_un_epca*0348913 Metron 0026-1424 2281-695X Roč. 77 č. 3 2019 253 270 Springer |
|