It is weeks of hard work and research that has come for their final evaluation. As the submission dates for the final code submission and the evaluations are approaching, I have been working hard to give the project the last few touch ups and structure to finally able to submit it.
I am glad to say that the project has been able to meet most of its functional requirements and only a few tests are left to consider. The project would be beneficial to a variety of people who will be working on time-series forecasting models. The automatic prediction of model parameters will help save a lot of time of the users who spend it on ‘Hit-and-Trial’ to find the best fitting model.
The major components of the project(as of now) include:
- Automatic model Selection for SARIMAX models.
- Automatic model selection for Exponential Smoothing models.
- Automatic box-cox transformation.(parameter prediction)
- Forecast and ForecastSet classes to hold and compare different time-series models.
- Time Series Cross Validation module.
Over the next few days, I’ll be working on robust testing of the different modules that I have created to strengthen this project.
I am highly excited to see this project to be merged in the statsmodels repository and be a part of its release.
The project files can be found at: