Bias in the intervention in prediction measure in random forests: illustrations and recommendations
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DOI: 10.1093/bioinformatics/bty959
Abstract: Motivation Random forests (RF) are fast, flexible and have become a standard tool in bioinformatics, particularly because they provide variable importance measures (VIM), which can be used to identify relevant features or perform variable selection.… read more here.
Keywords: random forests; prediction measure; intervention prediction;
Intervention in prediction measure: a new approach to assessing variable importance for random forests
Sign Up to like & getrecommendations! Published in 2017 at "BMC Bioinformatics"
DOI: 10.1186/s12859-017-1650-8
Abstract: BackgroundRandom forests are a popular method in many fields since they can be successfully applied to complex data, with a small sample size, complex interactions and correlations, mixed type predictors, etc. Furthermore, they provide variable… read more here.
Keywords: intervention prediction; importance; measure; variable importance ... See more keywords