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Hybrid system with spectral clustering and semi-supervised support vector machine and its application to credit risk assessment

Speaker: Tao Yu (SUSTech)
Time: Jan 19, 2024, 14:00-15:00
Location: M5024, College of Science Bldg.

Abstract: This paper introduces an innovative hybrid unsupervised classification method, termed the Two-Stage Hybrid System with Spectral Clustering and Semi-Supervised Support Vector Machine (TSC-SVM). This method adeptly tackles the unsupervised imbalance problem prevalent in credit risk assessment by focusing on global optimal solutions. Additionally, we present a multi-view combined unsupervised approach that effectively mines data for deeper insights and bolsters the robustness of label predictions by harmonizing discrepancies across three different perspectives.