2 papers
stat.ML2025
Marginal and Conditional Importance Measures from Machine Learning Models and Their Relationship with Conditional Average Treatment Effect
Mohammad Kaviul Anam Khan, Olli Saarela, Rafal Kustra
Interpreting black-box machine learning models is challenging due to their strong dependence on data and inherently non-parametric nature. This paper reintroduces the concept of im…
stat.ME2022
A Feature Selection Method that Controls the False Discovery Rate
Mehdi Rostami, Olli Saarela
The problem of selecting a handful of truly relevant variables in supervised machine learning algorithms is a challenging problem in terms of untestable assumptions that must hold…