CoClust: A Python Package for Co-Clustering
Co-clustering (also known as biclustering), is an important extension of cluster analysis since it allows to simultaneously group objects and features in a matrix, resulting in row and column clusters that are both more accurate and easier to interpret. This paper presents the theory underlying seve...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Foundation for Open Access Statistics
2019-03-01
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| Series: | Journal of Statistical Software |
| Subjects: | |
| Online Access: | https://www.jstatsoft.org/index.php/jss/article/view/3727 |
| _version_ | 1818891617980907520 |
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| author | François Role Stanislas Morbieu Mohamed Nadif |
| author_facet | François Role Stanislas Morbieu Mohamed Nadif |
| author_sort | François Role |
| collection | DOAJ |
| description | Co-clustering (also known as biclustering), is an important extension of cluster analysis since it allows to simultaneously group objects and features in a matrix, resulting in row and column clusters that are both more accurate and easier to interpret. This paper presents the theory underlying several effective diagonal and non-diagonal co-clustering algorithms, and describes CoClust, a package which provides implementations for these algorithms. The quality of the results produced by the implemented algorithms is demonstrated through extensive tests performed on datasets of various size and balance. CoClust has been designed to complete and easily interface with popular Python machine learning libraries such as scikit-learn. |
| first_indexed | 2024-12-19T17:43:40Z |
| format | Article |
| id | doaj.art-96d61ac21f8745ee979295c451ff1211 |
| institution | Directory Open Access Journal |
| issn | 1548-7660 |
| language | English |
| last_indexed | 2024-12-19T17:43:40Z |
| publishDate | 2019-03-01 |
| publisher | Foundation for Open Access Statistics |
| record_format | Article |
| series | Journal of Statistical Software |
| spelling | doaj.art-96d61ac21f8745ee979295c451ff12112022-12-21T20:12:09ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602019-03-0188112910.18637/jss.v088.i071278CoClust: A Python Package for Co-ClusteringFrançois RoleStanislas MorbieuMohamed NadifCo-clustering (also known as biclustering), is an important extension of cluster analysis since it allows to simultaneously group objects and features in a matrix, resulting in row and column clusters that are both more accurate and easier to interpret. This paper presents the theory underlying several effective diagonal and non-diagonal co-clustering algorithms, and describes CoClust, a package which provides implementations for these algorithms. The quality of the results produced by the implemented algorithms is demonstrated through extensive tests performed on datasets of various size and balance. CoClust has been designed to complete and easily interface with popular Python machine learning libraries such as scikit-learn.https://www.jstatsoft.org/index.php/jss/article/view/3727data miningco-clusteringpython |
| spellingShingle | François Role Stanislas Morbieu Mohamed Nadif CoClust: A Python Package for Co-Clustering Journal of Statistical Software data mining co-clustering python |
| title | CoClust: A Python Package for Co-Clustering |
| title_full | CoClust: A Python Package for Co-Clustering |
| title_fullStr | CoClust: A Python Package for Co-Clustering |
| title_full_unstemmed | CoClust: A Python Package for Co-Clustering |
| title_short | CoClust: A Python Package for Co-Clustering |
| title_sort | coclust a python package for co clustering |
| topic | data mining co-clustering python |
| url | https://www.jstatsoft.org/index.php/jss/article/view/3727 |
| work_keys_str_mv | AT francoisrole coclustapythonpackageforcoclustering AT stanislasmorbieu coclustapythonpackageforcoclustering AT mohamednadif coclustapythonpackageforcoclustering |