Daniel Schalk

Automatic Componentwise Boosting: An Interpretable AutoML System

2021 · arXiv (Cornell University)

In practice, machine learning (ML) workflows require various different steps, from data preprocessing, missing value imputation, model selection, to model tuning as well as model evaluation. Many of these steps rely on human ML experts. …