Confusion matrix and ROC curves, tenfold cross-validation experiment.

Confusion matrix and ROC curves, tenfold cross-validation experiment.

<p>Support vector machine (a), Decision tree (b), k-nearest neighbour (c), Naïve Bayes (d).</p>

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Bibliographic Details
Main Author:	Eslam Hamouda (5172083) (author)
Other Authors:	Mayada Tarek (5172080) (author)
Published:	2024
Subjects:	Medicine Genetics Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified universal rule guides grey wolf optimizer vast feature space first layer applies exploration ability allows statlog dna dataset given dna sequence reliable feature selection div >< p proposed method divides predicting junction type classification model trained feature selection second layer method using junction type generalization ability ensemble model proposed approach various partitions using cross thus leading thorough examination test sets study presents splicing regulation selected features rna splicing retrieved features remaining held proposed gwo implementation code hybrid approach gene structure finding suggests ensemble learning efficiently search disease causes computational biology comprehensively evaluating classifier ’ 96 %.
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