Global Epidemic Classification Based on K-Nearest Neighbor Algorithm

K-neighbor algorithm is an effective way to classify things according to their characteristics. Novel Coronavirus epidemic development and response situation of various countries around the world can be classified to simplify the difficulty of epidemic prevention and control and provide useful information for them. Based on the data of WHO and the existing research results at home and abroad, this paper analyzes the evaluation indexes of national epidemic situation, selects representative countries as training samples, and points out the epidemic situation types of corresponding countries. It aims to provide reference for relevant researchers in epidemic prevention and control and trend prediction through global epidemic classification, and hopes to improve relevant technologies in further research, so as to make the classification more scientific and accurate.