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CoClust: A Python Package for Co-Clustering
Author(s) -
François Role,
Stanislas Morbieu,
Mohamed Nadif
Publication year - 2019
Publication title -
journal of statistical software
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.636
H-Index - 145
ISSN - 1548-7660
DOI - 10.18637/jss.v088.i07
Subject(s) - python (programming language) , cluster analysis , computer science , biclustering , implementation , diagonal , row and column spaces , r package , cluster (spacecraft) , data mining , algorithm , computational science , row , programming language , artificial intelligence , fuzzy clustering , mathematics , cure data clustering algorithm , geometry
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.

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