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20162023
most citedRegularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features

168 citations · 656 across the 19 of their papers we have counts for

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cs.LG2023

Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models

Lennart Schneider, Bernd Bischl, Janek Thomas

We present a model-agnostic framework for jointly optimizing the predictive performance and interpretability of supervised machine learning models for tabular data. Interpretabilit…

cs.LG2023

MO-DEHB: Evolutionary-based Hyperband for Multi-Objective Optimization

Noor Awad, Ayushi Sharma, Philipp Muller +2

Hyperparameter optimization (HPO) is a powerful technique for automating the tuning of machine learning (ML) models. However, in many real-world applications, accuracy is only one…