ML

Machine learning is not the ideal tool for time series forecasting for a number of reasons, but, as I will demonstrate it in a future post, limited models can be built for short-term forecasting exercises. One aspect of time series data is, however, that you can’t split your observations randomly into train and test subsets: you train on an early interval and test on a later one. Standard ML libraries, such as scikit-learn, don’t provide a tool for that.