COVID-19 dataset comprises date, country, confirmed cases, recovered cases, total death. The data is integrated with climate data consisting of humidity, dew, ozone, perception, max temperature, minimum temperature, and UV. The artificial intelligence based COVID-19 diagnosis strategies can generate more accurate results, save radiologist time, and make the diagnosis process cheaper and faster than the usual laboratory techniques. The covid-19 detection has various phases which include pre-processing, feature extraction, classification and performance analysis. In this research work voting classification method is designed for the covid-19 prediction. It is analyzed that proposed model increase accuracy, precision and recall for the covid- 19 prediction.
Rohit Agarwal
Babu Banarasi Das University, India
Covid-19, Machine learning, Voting Classification, Feature Extraction | Published By :
ICTACT
Published In :
ICTACT Journal on Data Science and Machine Learning
( Volume: 2 , Issue: 4 )
Date of Publication :
September 2021
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