An implementation of the Random Cut Forest data structure for sketching streaming data, with support for anomaly detection, density estimation, imputation, and more.
Description of changes: RCF already provides a forecast/extrapolate functionality based on repeated estimation of the conditional median. This PR exposes the errors in the estimation of those conditional medians. They may be helpful in. estimating confidence bounds using model assumptions extraneous to the non-parametric estimation. In the next few PRs we would enable forecasting for TRCFs as well.
Description of changes: RCF already provides a forecast/extrapolate functionality based on repeated estimation of the conditional median. This PR exposes the errors in the estimation of those conditional medians. They may be helpful in. estimating confidence bounds using model assumptions extraneous to the non-parametric estimation. In the next few PRs we would enable forecasting for TRCFs as well.