ABSTRACT

Owing to enormous increase of Lung Cancer Cases Worldwide, primary diagnosis is not a feasible one for developing countries like India, which in turn increases the mortality rate. Early detection of lung cancer is also a challenging task for the clinicians, as there are no preliminary symptoms. Computer Aided Detection & Diagnostic (CADe & CADx) system acts as a supporting tool for lung cancer detection & diagnosis [1]. In this paper, a supporting diagnostic tool with ‘dbest’ Feature Selection method based on Support Vector Machine (SVM) model was presented. The parameters used in this study are: cross validation score, Randomized search and Grid search methods. By comparing the performance metrics of both Grid and Randomized Search, the Grid model outperforms the Randomized in terms of precision, recall and F1 score. Keywords: Cross – validation – score, Randomized Search, Grid Search, precision, recall, F1 Score
Publication date: 01/07/2023

https://ijbpas.com/pdf/2023/July/MS_IJBPAS_2023_7244.pdf

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https://doi.org/10.31032/IJBPAS/2023/12.7.7244