COVID-19 is an infection caused by a recently discovered corona virus. The symptoms of COVID-19 are fever, cough and dumpiness of breathing. A quick and accurate identification is essential for an efficient fight against COVID-19. A machine learning technique is initiated for categorizing the chest x-ray images into two cases, COVID-19 positive case or negative case. In this, Multiclass classifier optimized with flamingo search algorithm is utilized for COVID detection. Initially, the input data are selected from different states of India in chronological dates. Then the input data are classified using different machine learning classifier such as random forest, decision tree, and K-Nearest Neighbour. Generally Multiclass machine learning classifier does not reveal any adoption of optimization techniques for computing the optimal parameters for assuring accurate classification of COVID. Therefore, flamingo search algorithm is utilized to optimize the Multiclass machine learning classifier. Here decision tree optimized with flamingo search algorithm outperformed compared with other two machine learning classifier. So it is used for prediction and analysis of all COVID detection result.
Covid-19 dataset
Predicting high accuracy covid count
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