Evaluation metrics and statistical tests for machine learning

Research on different machine learning (ML) has become incredibly popular during the past few decades. However, for some researchers not familiar with statistics, it might be difficult to understand how to evaluate the performance of ML models and compare them with each other. Here, we introduce the...

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Veröffentlicht in:	Scientific reports Jg. 14; H. 1; S. 6086 - 14
Hauptverfasser:	Rainio, Oona, Teuho, Jarmo, Klén, Riku
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 13.03.2024 Nature Publishing Group Nature Portfolio
Schlagworte:	639/705/117 639/705/531 Accuracy Bronchopulmonary infection Classification Evaluation metrics Humanities and Social Sciences Image processing Image Processing, Computer-Assisted - methods Information processing Learning algorithms Lung cancer Machine Learning Mathematical models Medical images multidisciplinary Neural networks Neural Networks, Computer Performance evaluation Positron emission tomography Science Science (multidisciplinary) Statistical analysis Statistical testing Supervised Machine Learning Tomography X-rays Statistical testing Medical images Evaluation metrics Machine learning
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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