ENBIS Spring Meeting 2024

Session

Contributed session

16 May 2024, 10:00

Dortmund

Conveners

Contributed session: 3

• Jacqueline Asscher (Kinneret College)

51. Training Gradient Boosted Decision Trees on Tabular Data Containing Label Noise for Classification Tasks

Anita Eisenbürger (Debeka)

16/05/2024, 10:00

Spring Meeting

Label noise, the mislabeling of instances in a dataset, is harmful to classifier performance, increases model complexity, and impairs adequate feature selection. It is frequent in large scale datasets and naturally occurs when human experts are involved. While extensive research has focused on mitigating label noise in image and text datasets through deep neural networks, there exists a...

47. Why Order Matters for Ordinal Prediction with Random Forests

Philip Buczak (TU Dortmund University)

16/05/2024, 10:20

Spring Meeting

Traditionally, ordinal response data have been modeled through parametric models such as the proportional odds model. More recently, popular machine learning methods such as random forest (RF) have been extended for ordinal prediction. As RF does not inherently support ordinal response data, a common approach is assigning numeric scores to the ordinal response categories and learning a...