3 papers
cs.LG2023
The Conditioning Bias in Binary Decision Trees and Random Forests and Its Elimination
Gábor Timár, György Kovács
Decision tree and random forest classification and regression are some of the most widely used in machine learning approaches. Binary decision tree implementations commonly use con…
cs.CL2023
NLP-LTU at SemEval-2023 Task 10: The Impact of Data Augmentation and Semi-Supervised Learning Techniques on Text Classification Performance on an Imbalanced Dataset
Sana Sabah Al-Azzawi, György Kovács, Filip Nilsson +2
In this paper, we propose a methodology for task 10 of SemEval23, focusing on detecting and classifying online sexism in social media posts. The task is tackling a serious issue, a…
eess.SP2020
Overly Optimistic Prediction Results on Imbalanced Data: a Case Study of Flaws and Benefits when Applying Over-sampling
Gilles Vandewiele, Isabelle Dehaene, György Kovács +9
Information extracted from electrohysterography recordings could potentially prove to be an interesting additional source of information to estimate the risk on preterm birth. Rece…