This notebook trains an ensemble of ARIMA (Autoregressive integrated moving average) model and LSTM (Long Short Term Memory) to predict Web Traffic on Wiki Pages.
This is based on a time series problem on kaggle. We need to predict the traffic on Wiki Pages on certain dates.
The data provided here is available on kaggle.com https://www.kaggle.com/c/web-traffic-time-series-forecasting/data
We use statsmodels ARIMA model and keras LSTM RNN model to train our ensemble.
You can directly have a look at the kernel at https://www.kaggle.com/screech/ensemble-of-arima-and-lstm-model-for-wiki-pages
This is the form of data we will be getting. We convert it from csv to a pandas DataFrame.
Now we will visualize the data in form of a graph. These are the different pages on Wiki.
Now we train our ARIMA and LSTM models on this data and get the predictions.
In a similar way we train all ARIMA models. Rest of the graphs are available in the notebook.
In a similar way we train all LSTM models. Rest of the graphs are available in the notebook.