Machine Learning Students Overfit to Overfitting

Matias Valdenegro-Toro*, Matthia Sabatelli

*Corresponding author for this work

Research output: Working paperPreprintAcademic

144 Downloads (Pure)

Abstract

Overfitting and generalization is an important concept in Machine Learning as only models that generalize are interesting for general applications. Yet some students have trouble learning this important concept through lectures and exercises. In this paper we describe common examples of students misunderstanding overfitting, and provide recommendations for possible solutions. We cover student misconceptions about overfitting, about solutions to overfitting, and implementation mistakes that are commonly confused with overfitting issues. We expect that our paper can contribute to improving student understanding and lectures about this important topic.
Original languageEnglish
PublisherarXiv
Number of pages6
DOIs
Publication statusSubmitted - 7-Sept-2022

Keywords

  • overfitting
  • machine learning
  • teaching machine learning

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