There is indeed a vast literature on the design and analysis of decision tree algorithms that aim at optimizing these parameters. This paper contributes to this important line of research: we propose ...

Introduction Shared decision-making (SDM) requires that individuals are correctly and smoothly supported to make decisions. However, in Japan, development of decision aids (DAs) to support ...

This project implements a distributed machine learning pipeline to predict flight arrival delays with a Mean Absolute Error (MAE) of approximately 8 minutes. The ...

Abstract: The research uses the Ames dataset from Kaggle for predicting house prices. It applies six different machine learning models. These are XGBoost Regressor, Support Vector Regressor, Decision ...

Mr. Currell was a deputy undersecretary and senior adviser at the Department of Education from 2018 to 2021. He is a trustee of Gustavus Adolphus College in St. Peter, Minn. This week, about 200,000 ...

Abstract: In the practical application of machine learning, the opaqueness of models often poses significant challenges. While decision trees are known for balancing representability with ...