An unsupervised classifier system using soft graph colouring

Aim and Objective: Cancer is one of the deadliest diseases, taking the lives of millions every year. Traditional methods of treating cancer are expensive and toxic to normal cells. Fortunately, anti-cancer peptides (ACPs) can eliminate this side effect. However, the identification and development of new anti Materials and Methods: In our study, a multi-classifier system was used, combined with multiple machine learning models, to predict anti-cancer peptides. These individual learners are composed of different feature information and algorithms, and form a multi-classifier system by voting. Results and Conclusion: The experiments show that the overall prediction rate of each individual learner is above 80% and the overall accuracy of multi-classifier system for anti-cancer peptides prediction can reach 95.93%, which is better than the existing prediction model.

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Graph colouring variations

Topics in Algorithmic Graph Theory ◽

10.1017/9781108592376.005 ◽

2021 ◽

pp. 33-51

Author(s):

Alain Hertz ◽

Bernard Ries

Keyword(s):

Graph Colouring

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Misclassification detection based on conditional VAE for rule evolution in learning classifier system

Proceedings of the Genetic and Evolutionary Computation Conference Companion ◽

10.1145/3449726.3459508 ◽

2021 ◽

Author(s):

Hiroki Shiraishi ◽

Masakazu Tadokoro ◽

Yohei Hayamizu ◽

Yukiko Fukumoto ◽

Hiroyuki Sato ◽

...

Keyword(s):

Learning Classifier System ◽

Classifier System ◽

Learning Classifier

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The gender system of Longuda

Language Typology and Universals ◽

10.1515/stuf-2021-1035 ◽

2021 ◽

Vol 74 (2) ◽

pp. 327-346

Author(s):

Julius-Maximilian Elstermann ◽

Ines Fiedler ◽

Tom Güldemann

Keyword(s):

Historical Reconstruction ◽

Classifier System ◽

Class System ◽

Nominal Form ◽

Noun Class ◽

Nominal Classification ◽

Gender System

Abstract This article describes the gender system of Longuda. Longuda class marking is alliterative and does not distinguish between nominal form and agreement marking. While it thus appears to be a prototypical example of a traditional Niger-Congo “noun-class” system, this identity of gender encoding makes it look morpho-syntactic rather than lexical. This points to a formerly independent status of the exponents of nominal classification, which is similar to a classifier system and thus less canonical. Both types of class marking hosts involve two formally and functionally differing allomorphs, which inform the historical reconstruction of Longuda noun classification in various ways.

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