The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

Hello! I'm a dreamer focusing on high-load distributed systems and low-level engineering. I mainly code in Rust and Python ...

This set of notebooks enables the analysis of comorbidities associated with male infertility using structured EHR data. First, we identified nonoverlapping patients with male infertility and patients ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Abstract: This study introduces a novel approach to example selection in few-shot learning scenarios for dialog intent classification, leveraging logistic regression to refine the set of examples ...