Article

Class imbalance should not throw you off balance: Choosing the right classifiers and performance metrics for brain decoding with imbalanced data

2022-07-20

Abstract excerpt

Machine learning (ML) is increasingly used in cognitive, computational and clinical neuroscience. The reliable and efficient application of ML requires a sound understanding of its subtleties and limitations. Training ML models on datasets with imbalanced classes is a particularly common problem, and it can have severe consequences if not adequately addressed. With the neuroscience ML user in mind, this paper prov...

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Literature Corpus work: e3a424c0-bfce-52a6-946f-6f97be6c532f
DOI: 10.1101/2022.07.18.500262

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