Hello,
I have recently started using the time series models in data robot for monthly data of mine. I was able to train this data and get a model. However, when forecasting for future values, it is only doing so for 3 months into the future. How can I change this forecast distance/forecast window to encompass a larger range of months. Note I use python to communicate with the data robot api so an answer in python would be great. Thanks.
Here is the code
If you have a calendar that you want to use you can upload it to DataRobot this way
calendar = dr.CalendarFile.create('Acme_Calendar.csv',
calendar_name = 'US_Calendar')
def start_modeling(projectName,data_df):
'''provide a project name, and the dataframe for training
1. Create project
2. Set specifications for time-series modeling
3. Start project'''
project = dr.Project.create(project_name=projectName, sourcedata=data_df)
mySpec = dr.DatetimePartitioningSpecification(
datetime_partition_column=ts_settings['date_col'],
use_time_series=True,
multiseries_id_columns=[ts_settings['series_id']],
default_to_known_in_advance=False,
feature_derivation_window_start=ts_settings['fdw_start'],
feature_derivation_window_end= ts_settings['fdw_end'],
forecast_window_start=ts_settings['fd_start'],
forecast_window_end=ts_settings['fd_end'],
calendar_id=calendar.id
)
project.set_target(
target = ts_settings['target'],
partitioning_method = mySpec,
mode=dr.AUTOPILOT_MODE.FULL_AUTO ##### Here is where we can change to dr.AUTOPILOT_MODE.FULL_AUTO
)
project.wait_for_autopilot() ##Wait for autopilot to finish
return(project)
#Create and Start Project
project = start_modeling(ts_settings['project_name'],ts_settings['use_time_series'])
Also, you can find a full python solution for time-series in here
Hi netnet,
I think you could change the input values when you start configuration for Forecast Window,then go to Advanced Options -> Configure Backtesting to check forecasting future period.