Title :
RCMDE-GMD: Predicting gene ontology terms using differential evolution
Author :
Menezes, Rafael Abud ; Nievola, Julio Cesar
Author_Institution :
Programa de Pos Grad. em Inf., Pontificia Univ. Catolica do Parana, Curitiba, Brazil
Abstract :
In this paper, we present a method called RCMDE-GMD (Rule Construction Method Using Differential Evolution Global Multi-Directed Acyclic Graph). The main objective of RCMDE-GMD is to build multi-label global hierarchical classifiers with the hierarchy of classes represented by a DAG. Here, we compare RCMDE-GMD with HLCS-Multi (Hierarchical Learning Classifier System), a method based on Learning Classifier Systems, and with Clus-HMC (Hierarchical Multi-Label Classification), a method based on the induction of decision trees. In the experiments, RCMDE-GMD outperformed HLCS-Multi using one measure from all the datasets and outperformed Clus-HMC in some conditions.
Keywords :
bioinformatics; directed graphs; evolutionary computation; pattern classification; DAG; RCMDE-GMD; gene ontology term prediction; multilabel global hierarchical classifiers; rule construction method using differential evolution global multidirected acyclic graph; Decision trees; Evolution (biology); Hafnium; Nickel; Proteins; Sociology; Statistics; classes; classifiers; hierarchical; multi-label;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2014 11th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4799-5147-5
DOI :
10.1109/FSKD.2014.6980888