Conformal Prediction with Python (Uncertainty Quantification in Time Series Analysis)

Recently I discovered Conformal Prediction which in a nutshell gives you a prediction interval instead of a single point prediction for a given input.

As far as I understand it works like this (very simplified and I just started learning TS and CP so take everything I write with a grain of salt):

1. Choose forecasting model for single point prediction as usual (ARIMA, ES, NBEATS, NHiTS, etc.) and train.
2. Define significance level alpha (e.g. 0.1) so 90% of …

analysis datascience everything interval prediction python quantification series simplified time series uncertainty