Analysis and Comparison for Innovative Prediction Technique of COVID-19 using Support Vector Machine over Neural Network algorithm with Improved Accuracy
Abstract:Aim: The primary purpose of this study is to improve the accuracy of COVID-19 prediction and evaluation. Materials and Methods: This project is based on data extracted from Kaggle’s website, which is separated into two categories. According to the total sample size estimated by clinical.com, each group comprises 20 samples (N=20) for both the Support Vector Machine (SVM) and Neural Network methods, by keeping 0.05 alpha error-threshold, 95% confidence interval, enrolment ratio at 0:1, and G power at 80%. In Ma… Show more
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