GDL

Journal from gdlhub / 2021-09-04 15:47:59
Oleh : Micheal Olaolu Arowolo, Marion Olubunmi Adebiyi, Ayodele Ariyo Adebiyi, Telkomnika
Dibuat : 2021-02-04, dengan 1 file

Keyword : decision tree; genetic algorithm; KNN; mosquito anopheles; ribonucleic acid sequencing;
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/16381/9725
Sumber pengambilan dokumen : web

Malaria larvae accept explosive variable lifecycle as they spread across numerous mosquito vector stratosphere. Transcriptomes arise in thousands of diverse parasites. Ribonucleic acid sequencing (RNA-seq) is a prevalent gene expression that has led to enhanced understanding of genetic queries. RNA-seq tests transcript of gene expression, and provides methodological enhancements to machine learning procedures. Researchers have proposed several methods in evaluating and learning biological data. Genetic algorithm (GA) as a feature selection process is used in this study to fetch relevant information from the RNA-Seq Mosquito Anopheles gambiae malaria vector dataset, and evaluates the results using kth nearest neighbor (KNN) and decision tree classification algorithms. The experimental results obtained a classification accuracy of 88.3 and 98.3 percents respectively.

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