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.

Links

• Hands-On Unsupervised Learning Using Python More detailed analysis in a book I read about unsupervised learning.

Thoughts

• This is a topic I would love to explore more about.