PCA SVM and Xgboost Algorithms for Covid-19 Recognition in Chest X-Ray Images

Abstract

AbstractCovid-19 is a life-threatening epidemic, which makes it an active research topic. Our work aims to use the power of Machine Learning algorithms to develop an intelligent system for recognition of covid-19 in chest X-ray images. In this paper, we proposed a hybrid model based Principal Component Analysis (PCA) technique, Support Vector Machine (SVM) and Xgboost algorithms for Covid-19 recognition in chest X-ray images. Our method merges the best properties of PCA and SVM to perform the recognition process. The PCA algorithm used to extract features from X-ray images, SVM implemented as a binary classifier and finally Xgboost used to boost the effectiveness of our model and to avoid the overfitting. Our model shows a satisfactory result with less complex model architecture.KeywordsMachine learningSupport Vector Machine (SVM)Principal Component Analysis (PCA)Covid-19Xgboost algorithmX-ray chest images