AutoML Forecasting
AutoML (Machine Learning) forecasting leverages Oracle Data Science, employing meta-learning to quickly identify the most relevant features, model and hyper-parameters for a given training dataset. Forecast and model are precomputed and the forecasts are periodically retrained.
AutoML's forecasting selects the best fit from multiple machine learning models trained on fixed data windows. The forecast uses up to 13 months of data, or the highest amount of data available for a resource if the resource has less than 13 months since onboarding. AutoML utilizes daily data and is only available within a single resource scope (single host or database).
AutoML forecasting is located within the Trend & Forecast chart, click on the AutoML forecasting button. A new pop up will appear with the AutoML forecasting charts loaded. It will state the training period and the selected forecast algorithms for maximum usage and average usage. The maximum and average confidence channels are also displayed within the chart. The confidence interval for these are 95%, meaning that 95% of future points are expected to fall within this radius from the forecast.
Figure 3-5 AutoML forecasting Chart
Note
The slider is a viewport selector.
The slider is a viewport selector.
To learn more about AutoML see: AutoMLx.