tut11

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Last edited Feb 14, 2020

Created on Feb 13, 2020

This example shows the variable importance results from a Boruta random forest feature selection analysis, displaying which predictors are confirmed, tentative, or rejected as significant. The plot renders a boxplot-style visualization of variable importance scores, with the Boruta output object passed to the base R `plot()` function. The code first extracts the names of confirmed and tentative variables using the `names()` and `%in%` operators on the `finalDecision` vector, then prints them. The visualization uses R’s standard graphics API, with `cex.axis`, `las`, and `main` parameters adjusting label size, orientation, and title.

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