2021
DOI: 10.21203/rs.3.rs-563410/v1
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Automated Feature Selection and Classification for High-Dimensional Biomedical Data

Abstract: Background: Automated machine learning aims to automate the building of accurate predictive models, including the creation of complex data preprocessing pipelines. Although successful in many fields, they struggle to produce good results on biomedical datasets, especially given the high dimensionality of the data. Result: In this paper, we explore the automation of feature selection in these scenarios. We analyze which feature selection techniques are ideally included in an automated system, determine how to e… Show more

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