Random Forest (page 3 of 5)

A single decision tree model made from a single training data set can make a decent (low bias) predictive model. Additionally, they are significantly less "blackbox" than a random forest trained model. However, single pruned decision trees may not be as accurate as we would like and deep trees (i.e., large depth) may be subject to overfitting (high variance) due to their complexity & idiosyncratic nature.