Score Timeseries
This module is to score the previously trained module using "Train Score Time Series" module
This experiment has 3 new modules that helps create forecast for time series data
- **Train and Score time series** data using R time series library. This module asks users to provide dataset with historical values, provide number of forecast points, seasonality period, and forecast algorithm (Arima, ETS, STL)
- **Scoring time series** accepts input as serialized model with number of forecast periods. This module forecasts future periods based on the model and requested number of periods
- **Evaluate time series** - this accepts dataset with observed and forecast values to generate performance metrics such as RMSE and plot actual vs. forecast
### Score Time Series Module ###
This module accepts serialized model as an input that is previously trained using Train/Score. This module requires only a single setting that is number of predictions to be generated.
This module generates forecast data, low/high 80% confidence interval, and low/high 95% confidence interval.

### Overall Experiment ###

### Source code for modules ###
The source code for this is located at [https://gist.github.com/nk773/af9bb2caf92bb23b95bac873312a5269](https://gist.github.com/nk773/af9bb2caf92bb23b95bac873312a5269)