Abstract
A novel coronavirus (SARS-CoV-2) is an unusual viral pneumonia in patients, first found in late December 2019, latter it declared a pandemic by World Health Organizations because of its fatal effects on public health. In this present, cases of COVID-19 pandemic are exponentially increasing day by day in the whole world. Here, we are detecting the COVID-19 cases, i.e., confirmed, death, and cured cases in India only. We are performing this analysis based on the cases occurring in different states of India in chronological dates. Our dataset contains multiple classes so we are performing multi-class classification. On this dataset, first, we performed data cleansing and feature selection, then performed forecasting of all classes using random forest, linear model, support vector machine, decision tree, and neural network, where random forest model outperformed the others, therefore, the random forest is used for prediction and analysis of all the results. The K-fold cross-validation is performed to measure the consistency of the model.
Highlights
The virus of coronaviruses (CoV) is a special kind of virus that itself is a disease and it enhances the existing disease in humans body which makes it a very dangerous virus
This paper proposes machine learning schemes based on a data-driven approach
This paper proposes a model, which can forecast the count of fresh COVID-19 cases, so that the management can make a preparation to handle these cases
Summary
The virus of coronaviruses (CoV) is a special kind of virus that itself is a disease and it enhances the existing disease in humans body which makes it a very dangerous virus This virus results in wheezing, hard to breathe, bad digestive system, and liverwort, effects badly human nervous system (center), and harms animals like cows, horses, and pigs that are kept, raised, and used by people and different wild animals. In India, the first case of coronavirus disease 2019 (COVID-19) was announced on 30th January 2020 This virus extends to the whole of India (in their different districts) till April 2020 end. The different parts of this virus are introduced in this diagram[3] The objectives of this surveillance are the following: (1) Monitor trends in COVID-19 disease at national levels. The objectives of this surveillance are the following: (1) Monitor trends in COVID-19 disease at national levels. (2) Rapidly detect new cases in countries where the virus has started to circulate and monitor cases in countries where the virus is not circulating. (3) Provide epidemiological information to conduct risk assessments at the national and state level. (4) Provide epidemiological information to guide preparedness and response measures
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