@article{article_1039544, title={A 21st Century Approach in Analysing Health Precautions in London with Machine Learning Driven Data Mining}, journal={Avrupa Bilim ve Teknoloji Dergisi}, pages={101–106}, year={2021}, DOI={10.31590/ejosat.1039544}, author={Yavuz, Özerk}, keywords={Health Restriction, Health Precaution, Covid-19, Pandemy, Epidemy, Clustering, Classification, Data Mining, Machine Learning, Quantitative Analysis, Supervised Learning, Unsupervised Learning}, abstract={As in the past, today preventive treatments and health policies constitute an important role in combatting with several diseases, medical phenomenon like pandemies or epidemies. These approaches can prevent several health focused negative consequences in early stages or can give leaders and medical professionals advantage in managing risks associated with health concerns. Usually effective usage of early warning systems, analysis of historical data for exploratory and confirmatory understanding may provide several advantages in this context. In this study a historical data analysis has been applied to understand similar phenomena with the help of machine learning driven data mining. Clustering and classification performances and rules generated by these approaches have also been assessed.}, number={32}, publisher={Osman SAĞDIÇ}