r/MachineLearning - [P] Time Series Analysis - Predicting Electricity Consumption using an LSTM network

So, I compared the model with ARIMA and a few interesting findings. Firstly, there doesn't appear to be any seasonal component in the data - when decomposed with statsmodels, the series simply shows a straight line. Also, ARIMA showed a mean percentage error of 23%, whereas for LSTM it was just over 8%. The daily fluctuations in electricity consumption is quite volatile, so it looks like LSTM has an advantage over ARIMA here in that it is accounting for the inherent volatility in the series. While ARIMA would usually need to be combined with a model such as GARCH to estimate this volatility, the inherent nature of LSTM allows it to handle sequential data and in this case it looks like it's handling the volatility quite well.