A comparative study of FCA-based supervised classification algorithms

Huaiyu Fu; Huaiguo Fu; Patrik Njiwoua; Engelbert Mephu Nguifo

doi:10.1007/978-3-540-24651-0_26

A comparative study of FCA-based supervised classification algorithms

Huaiyu Fu, Huaiguo Fu, Patrik Njiwoua, Engelbert Mephu Nguifo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

15 Citations (Scopus)

Abstract

Several FCA-based classification algorithms have been proposed, such as GRAND, LEGAL, GALOIS, RULEARNER, CIBLe, and CLNN & CLNB. These classifiers have been compared to standard classification algorithms such as C4.5, Naïve Bayes or IB1. They have never been compared each other in the same platform, except between LEGAL and CIBLe. Here we compare them together both theoretically and experimentally, and also with the standard machine learning algorithm C4.5. Experimental results are discussed.

Original language	English
Title of host publication	Concept Lattices
Editors	Peter Eklund
Publisher	Springer
Pages	313-320
Number of pages	8
ISBN (Print)	3540210431, 9783540210436
DOIs	https://doi.org/10.1007/978-3-540-24651-0_26
Publication status	Published - 2004
Externally published	Yes
Event	2nd International Conference on Formal Concept Analysis, ICFCA 2004 - Sydney, Australia Duration: 23 Feb 2004 → 26 Feb 2004

Publication series

Name	Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume	2961
ISSN (Print)	0302-9743

Conference

Conference	2nd International Conference on Formal Concept Analysis, ICFCA 2004
Country/Territory	Australia
City	Sydney
Period	23/02/2004 → 26/02/2004

Access to Document

10.1007/978-3-540-24651-0_26

Cite this

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title = "A comparative study of FCA-based supervised classification algorithms",

abstract = "Several FCA-based classification algorithms have been proposed, such as GRAND, LEGAL, GALOIS, RULEARNER, CIBLe, and CLNN & CLNB. These classifiers have been compared to standard classification algorithms such as C4.5, Na{\"i}ve Bayes or IB1. They have never been compared each other in the same platform, except between LEGAL and CIBLe. Here we compare them together both theoretically and experimentally, and also with the standard machine learning algorithm C4.5. Experimental results are discussed.",

author = "Huaiyu Fu and Huaiguo Fu and Patrik Njiwoua and {Mephu Nguifo}, Engelbert",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2004.; null ; Conference date: 23-02-2004 Through 26-02-2004",

year = "2004",

doi = "10.1007/978-3-540-24651-0_26",

language = "English",

isbn = "3540210431",

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Fu, H, Fu, H, Njiwoua, P & Mephu Nguifo, E 2004, A comparative study of FCA-based supervised classification algorithms. in P Eklund (ed.), Concept Lattices. Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), vol. 2961, Springer, pp. 313-320, 2nd International Conference on Formal Concept Analysis, ICFCA 2004, Sydney, Australia, 23/02/2004. https://doi.org/10.1007/978-3-540-24651-0_26

A comparative study of FCA-based supervised classification algorithms. / Fu, Huaiyu; Fu, Huaiguo; Njiwoua, Patrik et al.

Concept Lattices. ed. / Peter Eklund. Springer, 2004. p. 313-320 (Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science); Vol. 2961).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Several FCA-based classification algorithms have been proposed, such as GRAND, LEGAL, GALOIS, RULEARNER, CIBLe, and CLNN & CLNB. These classifiers have been compared to standard classification algorithms such as C4.5, Naïve Bayes or IB1. They have never been compared each other in the same platform, except between LEGAL and CIBLe. Here we compare them together both theoretically and experimentally, and also with the standard machine learning algorithm C4.5. Experimental results are discussed.

AB - Several FCA-based classification algorithms have been proposed, such as GRAND, LEGAL, GALOIS, RULEARNER, CIBLe, and CLNN & CLNB. These classifiers have been compared to standard classification algorithms such as C4.5, Naïve Bayes or IB1. They have never been compared each other in the same platform, except between LEGAL and CIBLe. Here we compare them together both theoretically and experimentally, and also with the standard machine learning algorithm C4.5. Experimental results are discussed.

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BT - Concept Lattices

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A comparative study of FCA-based supervised classification algorithms

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