I’m experimenting with Azure AutoML for timeseries forecasting. I have a simple two column training dataset with two years of data at hourly intervals. Column 1 is Date/Time Column 2 is the variable I want to predict. I’ve done several runs of Azure AutoML and it seems to complete successfully. However, when I do a forecast and graph it something is obviously wrong. It looks like the forecast is being quantised somehow. The graph below is for the 7 days after the training set. Blue is actual and red is the forecast. This is obviously not right.
Here is my configuration for the training (python):
lags = (1,24,168)
forecast_horizon = 7 * 24 # 7 days of hourly data
forecasting_parameters = ForecastingParameters(
automl_config = AutoMLConfig(task='forecasting',
verbosity = logging.INFO,
The best model from the run is a VotingEnsemble: