Forecast future values

With the Forecast future values task, you can predict the future values in a time-series of numerical observations. For example, you can predict future sales given the records of past ones.

Read the Forecasting tutorial to see an example of application of the forecasting task.

The forecast task expects values to be sorted by date and sampled at regular intervals, for example, each day, each week, or each month. The first column must contain dates. The next columns must contain one or more series of values. The first row must contain the name of the series. All the series must have the same number of values/rows. The Forecast future values task will predict values in any row that has a date but doesn’t have values.

Following is an example of a sheet compatible with the forecasting task. The forecasting task will predict the values of series A, B and C for the dates 2022-04-05 and 2022-04-06.

Date	A	B	C
2022-04-01	112	125	150
2022-04-02	118	149	178
2022-04-03	132	170	163
2022-04-04	129	170	172
2022-04-05
2022-04-06

Forecasting multiple series

By default, series (columns) are forecasted independently. Alternatively, it is possible to forecast them together. Predicting series of a similar nature together likely yields more accurate forecasts.

To forecast series together, provide one or more categorical values for each of the series. Series with similar categorical values will be forecasted together using a hierarchical reconciliation algorithm.

Note: The reconciliation algorithm used is a top-down using forecast proportions.

The next example shows the sales of 5 different products. Under the product name, the type, and the category of each product are indicated in the first two rows.

Date	Lemonade	Orange Juice	White Wine	Analog watch	Digital watch
Category	drink	drink	drink	wearable	wearable
Type	soda	soda	wine	watch	watch
2022-04-01	112	125	243	150	211
2022-04-02	118	149	264	178	180
2022-04-03	132	170	272	163	201
2022-04-04	129	170	237	172	204
2022-04-05
2022-04-06

Here, Lemonade and Orange Juice are both soda and drink. Both products are serving the same purpose (those are called substitution products) and probably have similar sales trends (e.g., increase sales in summer). White Wine is also a drink, but it is not a soda.

How are values forecasted

The algorithm used is a tuned model with cleaning, holiday, seasonality and trend structure. Look at the Advanced option section for the Forecast future values task. Details of the algorithms are described in Forecasting: Principles and Practice by Hyndman et al.