Publication Date: 2023/12/28
Abstract: There are numerous approaches for handling microarray gene expression data since new feature selection techniques are constantly being developed. To create a new subset of pertinent features, feature selection (FS) is utilized to pinpoint the essential feature subset. The model that used the informative subset projected that a classification model generated solely using this subset would have higher predicted accuracy than a model developed using the whole collection of attributes. We offer an analytical approach for cancer classification and developed a model using Support Vector Machine as classifier and after that Convolutional Neural Network in the aspect of Deep Learning. The outcome received in the context of the proposed model is very impressive and accurate.
Keywords: Feature selection; Optimization;Classification; Support Vector Machine (SVM); Deep Learning; Machine Learning; Convolutional Neural Network (CNN).
DOI: https://doi.org/10.5281/zenodo.10438850
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23DEC1319.pdf
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