Does Feature Selection Improve Classification? A Large Scale Experiment in OpenML

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Benchmark and Survey of Automated Machine Learning Frameworks (2019, methodology): “Using information on which preprocessing and model combination performs well, potentially better performing pipelines can be favored (Post et al., 2016; Bilalli et al., 2017; Schoenfeld et al., 2018).”
Meta-Learning: A Survey (2018, neutral): “Other approaches give recommendations for certain pipeline steps [118, 163], and can be leveraged in larger pipeline construction approaches, such as planning [55, 74, 105, 184] or evolutionary techniques [110, 164].”
OpenML: An R package to connect to the machine learning platform OpenML (2017, background): “Another beneﬁt is that linking one’s results to those of others has a large potential for new discoveries (Feurer et al, 2015; Post et al, 2016; Probst et al, 2017), leading to more publications and more collaboration with other scientists all over the world.”