7 citations · 35 across the 14 of their papers we have counts for
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cs.LG2022★ 3 cited
FOLD-SE: An Efficient Rule-based Machine Learning Algorithm with Scalable Explainability
Huaduo Wang, Gopal Gupta
We present FOLD-SE, an efficient, explainable machine learning algorithm for classification tasks given tabular data containing numerical and categorical values. FOLD-SE generates…
cs.LG2022
FOLD-TR: A Scalable and Efficient Inductive Learning Algorithm for Learning To Rank
Huaduo Wang, Gopal Gupta
FOLD-R++ is a new inductive learning algorithm for binary classification tasks. It generates an (explainable) normal logic program for mixed type (numerical and categorical) data.…
cs.LG2022★ 1 cited
FOLD-RM: A Scalable, Efficient, and Explainable Inductive Learning Algorithm for Multi-Category Classification of Mixed Data
Huaduo Wang, Farhad Shakerin, Gopal Gupta
FOLD-RM is an automated inductive learning algorithm for learning default rules for mixed (numerical and categorical) data. It generates an (explainable) answer set programming (AS…