Bootstrap Matrix & OOB Convergence

Every tree in a bagged ensemble — random forests included — is trained on its own bootstrap resample: N rows drawn with replacement from N original training rows. This simulator draws that bootstrap sample as a lit-up grid of the training rows themselves, then plots a live convergence chart of the cumulative out-of-bag fraction against its theoretical limit — (1 − 1/N)^N, which approaches 1/e ≈ 36.8% as the dataset grows — alongside a histogram comparing the empirical draw-count distribution to the Poisson(1) limit random forests rely on for their internal, honest estimate of generalization error.