Konu "Feature selection" için Bilgisayar Mühendisliği Bölümü Koleksiyonu listeleme
Toplam kayıt 6, listelenen: 1-6
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Evaluation of hybrid classification approaches: Case studies on credit datasets
(SPRINGER, 2018)Hybrid classification approaches on credit domain are widely used to obtain valuable information about customer behaviours. Single classification algorithms such as neural networks, support vector machines and regression ... -
Identifying Taxonomic Biomarkers of Colorectal Cancer in Human Intestinal Microbiota Using Multiple Feature Selection Methods
(Institute of Electrical and Electronics Engineers Inc., 2022)A variety of bacterial species called gut microbiota work together to maintain a steady intestinal environment. The gastrointestinal tract contains tremendous amount of different species including archaea, bacteria, fungi, ... -
Inflammatory bowel disease biomarkers of human gut microbiota selected via different feature selection methods
(PEERJ INC, 2022)The tremendous boost in next generation sequencing and in the “omics” technologies makes it possible to characterize the human gut microbiome—the collective genomes of the microbial community that reside in our gastrointestinal ... -
A noise-aware feature selection approach for classification
(SPRINGERONE NEW YORK PLAZA, SUITE 4600 , NEW YORK, NY 10004, UNITED STATES, 2021)A noise-aware version of support vector machines is utilized for feature selection in this paper. Combining this method and sequential backward search (SBS), a new algorithm for removing irrelevant features is proposed. ... -
PriPath: identifying dysregulated pathways from differential gene expression via grouping, scoring, and modeling with an embedded feature selection approach
(BMC, 2023)BackgroundCell homeostasis relies on the concerted actions of genes, and dysregulated genes can lead to diseases. In living organisms, genes or their products do not act alone but within networks. Subsets of these networks ... -
Review of feature selection approaches based on grouping of features
(PeerJ Inc., 2023)With the rapid development in technology, large amounts of high-dimensional data have been generated. This high dimensionality including redundancy and irrelevancy poses a great challenge in data analysis and decision ...