Creation and Research of HSE Entrants Portraits Compared to Historical Data

Student: Chizhova Daria

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2019

This is a research in Educational Data Mining field. It contains data preprocessing for statistical analysis. Applications and survey analysis of Higher School of Economics applicants using Machine Learning methods. Such methods of clusterization were applied as K-means, DBSCAN and hierarchical clustering HDBSCAN. The aim is to identify groups of applicants united by common features. Special characteristics describing the group of HSE enrollers were identified. The results of the exploratory analysis of applicants can be discussed by experts of the field and can be used for further research on student behavior and academic performance.

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