ListarGI-GAC - Artigos por tema "Mutual information"
Mostrando ítems 1-5 de 5
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CUDA acceleration of MI-based feature selection methods
(Elsevier, 2024-08)[Abstract]: Feature selection algorithms are necessary nowadays for machine learning as they are capable of removing irrelevant and redundant information to reduce the dimensionality of the data and improve the quality of ... -
Fast search of third-order epistatic interactions on CPU and GPU clusters
(Sage Publications Ltd., 2019-05-27)[Abstract] Genome-Wide Association Studies (GWASs), analyses that try to find a link between a given phenotype (such as a disease) and genetic markers, have been growing in popularity in the recent years. Relations between ... -
GPU-accelerated exhaustive search for third-order epistatic interactions in case–control studies
(Elsevier Ltd, 2015)[Abstract] Interest in discovering combinations of genetic markers from case–control studies, such as Genome Wide Association Studies (GWAS), that are strongly associated to diseases has increased in recent years. Detecting ... -
High-speed exhaustive 3-locus interaction epistasis analysis on FPGAs
(Elsevier B.V., 2015-07)[Abstract]: Epistasis, the interaction between genes, has become a major topic in molecular and quantitative genetics. It is believed that these interactions play a significant role in genetic variations causing complex ... -
Parallel-FST: A feature selection library for multicore clusters
(Elsevier, 2022-11)[Abstract]: Feature selection is a subfield of machine learning focused on reducing the dimensionality of datasets by performing a computationally intensive process. This work presents Parallel-FST, a publicly available ...
