6 citations · 6 across the 3 of their papers we have counts for
3 papers
MINERVA: Mutual Information Neural Estimation for Supervised Feature Selection
Taurai Muvunza, Egor Kraev, Pere Planell-Morell +1
Existing feature filters rely on statistical pair-wise dependence metrics to model feature-target relationships, but this approach may fail when the target depends on higher-order…
Shap-Select: Lightweight Feature Selection Using SHAP Values and Regression
Egor Kraev, Baran Koseoglu, Luca Traverso +1
Feature selection is an essential process in machine learning, especially when dealing with high-dimensional datasets. It helps reduce the complexity of machine learning models, im…
OTLP: Output Thresholding Using Mixed Integer Linear Programming
Baran Koseoglu, Luca Traverso, Mohammed Topiwalla +2
Output thresholding is the technique to search for the best threshold to be used during inference for any classifiers that can produce probability estimates on train and testing da…