time series prediction using LSTM Hi I have fairly very short time series data. The data set has number of systems $s_{1}, s_{2}, s_{3},..s_{n}$. For each $s_{i}$ we have recorded number of failures on each day. As of now, we have recorded 30 days. I would like to know can I use LSTM for predicting number of system failures for next day.
How about using Vector Auto Regression?. Any starting pointers and code references will be useful. Thank you.
Yes, LSTMs are fairly used in time series prediction. They can even handle missing data which is quite common in timeseries: Learning to diagnose with LSTM recurrent neural network. Still, I don't recommend starting directly with LSTM as the training takes time and you have to try many parameters to find the best that fits your data. You should start with some basic regressors like RandomForest or XGBoost.