2 citations · 2 across the 5 of their papers we have counts for
5 papers
A Data-Driven Approach to Support Clinical Renal Replacement Therapy
Alice Balboni, Luis Escobar, Andrea Manno +5
This study investigates a data-driven machine learning approach to predict membrane fouling in critically ill patients undergoing Continuous Renal Replacement Therapy (CRRT). Using…
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…
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…
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…
On multivariate randomized classification trees: -based sparsity, VC~dimension and decomposition methods
Edoardo Amaldi, Antonio Consolo, Andrea Manno
Decision trees are widely-used classification and regression models because of their interpretability and good accuracy. Classical methods such as CART are based on greedy approach…