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Predictive models are statistical models whose primary purpose is to predict other observations of a system optimally, as opposed to models whose purpose is to test a particular hypothesis or explain a phenomenon mechanistically. As such, predictive models place less emphasis on interpretability and more emphasis on performance.
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randomForest::varImp VS conditional variable importance [closed]
Data:
My training set consists of ~450k obs and 26 variables, out of which 1 is an ordinal factor (order_month, 12 levels) and the rest is numerical. Moreover, some of my predictors are highly corre …
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Random Forest Models: creating correlated features
I'm trying to understand how correlated (multicollinear) predictors affect predictive power and / or variable importance in tree models, e.g. Random Forest models. Particularly, I'd like to know if ce …