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We propose the use of Differential Evolution algorithm for the weight adjustment of base classifiers used in weighted voting heterogeneous ensemble of classifier. Average Matthews Correlation Coefficient (MCC) score, calculated over 10-fold cross-validation, has been used as the measure of quality of an ensemble. DE/rand/1/bin algorithm has been utilised to maximize the average MCC score calculated using 10-fold cross-validation on training dataset. The voting weights of base classifiers are optimized for the heterogeneous ensemble of classifiers aiming to attain better generalization performances on testing datasets.

SuRankCo is a machine learning based software to score and rank contigs from de novo assemblies of next generation sequencing data. It trains with alignments of contigs with known reference genomes and predicts scores and ranking for contigs which have no related reference genome yet. For more details about SuRankCo and its functioning, please see "SuRankCo: Supervised Ranking of Contigs in de novo Assemblies" Mathias Kuhring, Piotr Wojtek Dabrowski, Andreas Nitsche and Bernhard Y. ...

Rastreie.me Mestrado Profissional em Computação Aplicada UTFPR Dissertação de Mestrado Jean Pierobom jean@pierobom.com

Este projeto objetiva a criação de um Toolbox para utilização de algoritmos de Computação Bioinspirada. O Toobox oferece uma vasta coleção de algoritmos de ferramentas para o projeto de Algoritmos Genéticos e Redes Neurais.