Speaker
Dr
Andrea Carta
(University of Cagliari)
Description
SVM Regression Oblique Trees: A Novel Approach to Regression Tasks. This technique combines feature selection based on predictor correlation and a weighted support vector machine classifier with a linear kernel. Evaluation on simulated and real datasets reveals the superior performance of the proposed method compared to other oblique decision tree models, with the added advantage of enhanced interpretability.
Type of presentation | Talk |
---|---|
Classification | Both methodology and application |
Keywords | Decision Trees, Oblique Trees, Support Vector Machine |
Primary authors
Dr
Andrea Carta
(University of Cagliari)
Dr
Giulia Contu
(University of Cagliari)
Luca Frigau
(University of Cagliari)