Binary classification with the use of machine learning algorithms (Logit, k Nearest Neighbours, Suppoer Vector Machine) with the over-sampling SMOTE method

The aim of the paper is to implement the Market Basket Analysis (MBA) association rules to the case study of the grocery shop retail data. This unsupervised learning method shows the patterns is which one items (products) and linked with others. The rule “if - then” gives the clarification of the common behaviour of the subject which makes the decision, for instance, if one bought the bread, then he/she with some likelihood will buy also the butter. This example seems to be not a “rocket science”, however, the the MBA tool gives the deeper insight into the other dependencies between the purchased products

The aim of the paper is to find the possibilities in dimension reduction of Covid-19 illness symptoms and group the coexisting symptoms within the clusters. The dimension reduction procedure was done with the use of Principal Component Analysis (PCA) and further with the Multiple Correspondence Analysis (MCA). Clustering procedure was done according to the hierarchical clustering method.