Random Forest Crash Course: How Bagging Works and Where It Fails

Data scientist mdancho84 shared a crash course on random forests: trees train on bootstrapped subsets, combining predictions via majority vote (classification) or averaging (regression). In practice they beat penalized logistic regression on classification metrics but easily overfit on time series.

2026-10-12 ~ 2026-10-12 · 4 related posts

• Random Forest in 3 minutes: a data scientist distills 3 weeks of research — mdancho84 · 2026-10-12
• Bagging explained: each Random Forest tree trains on a random data subset — mdancho84 · 2026-10-12
• How Random Forest combines predictions: majority voting vs averaging — mdancho84 · 2026-10-12
• Random Forest beat penalized logistic regression on lead scoring, but overfits time series — mdancho84 · 2026-10-12