3 papers
cs.LG2025
Binary Kernel Logistic Regression: a sparsity-inducing formulation and a convergent decomposition training algorithm
Antonio Consolo, Andrea Manno, Edoardo Amaldi
Kernel logistic regression (KLR) is a widely used supervised learning method for binary and multi-class classification, which provides estimates of the conditional probabilities of…
cs.LG2025
Soft decision trees for survival analysis
Antonio Consolo, Edoardo Amaldi, Emilio Carrizosa
Decision trees are popular in survival analysis for their interpretability and ability to model complex relationships. Survival trees, which predict the timing of singular events u…
cs.LG2025
Soft regression trees: a model variant and a decomposition training algorithm
Antonio Consolo, Edoardo Amaldi, Andrea Manno
Decision trees are widely used for classification and regression tasks in a variety of application fields due to their interpretability and good accuracy. During the past decade, g…