Unsupervised Learning
Random Cut Forrest
Random Cut Forrest can be applied to solve problems within time series analysis. It is used to detect anomalies, seasonality, and breaks in seasonality. It might be relevant within the data cleaning segment as well. It is an AWS-developed model.