Random Forests for Change Point Detection. (arXiv:2205.04997v1 [stat.ME])

We propose a novel multivariate nonparametric multiple change point detection
method using classifiers. We construct a classifier log-likelihood ratio that
uses class probability predictions to compare different change point
configurations. We propose a computationally feasible search method that is
particularly well suited for random forests, denoted by changeforest. However,
the method can be paired with any classifier that yields class probability
predictions, which we illustrate by also using a k-nearest neighbor classifier.
We provide theoretical results motivating our choices. In …

arxiv change detection random random forests