Feature Selection with Boruta Part 2: Model Building
Continuing on from Part 1, I build random forest models on the processed aptamer data with the goal of minimizing out-of-bag error rate, while also reducing the number of features from over a thousand to a more managable number. Boruta will allow us to do both for a 83% of molecules in the data.