Clustering feedback data with Logistic Network Lasso
Simone Desogus
Clustering feedback data with Logistic Network Lasso.
Rel. Barbara Caputo. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2020
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Abstract
Feedback gathered from university courses' are the most effective tool given to students to shape lectures according to their needs and difficulties. Nonetheless, feedback is often neglected by both students and teachers, even if studies show how feedback can improve the quality of the student's experience as well as being an essential tool for the teacher's development. With the improvement in Natural Language Processing and the Machine Learning field, it is now possible to analyze text and effortlessly gather insights. These insights ease the professor's work when faced with the task of reading feedback which, depending on the course, can be thousands.
The Logistic Network Lasso is a novel semi-supervised machine learning algorithm that has been applied in the binary classification scenario and compared to algorithms such as Maxflow and Belief Propagation, resulting in overall increased accuracy
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