Prophet Cross Validator

Type

ml-predict

Class

fire.nodes.ts.NodeProphetCrossValidation

Fields

Name	Title	Description
horizon	Horizon	String with pd.Timedelta compatible style, e.g., ‘5 days’,’3 hours’, ‘10 seconds’.
period	Period	String with pd.Timedelta compatible style. Simulated forecast will be done at every this period. If not provided, 0.5 * horizon is used.
initial	Initial	String with pd.Timedelta compatible style. The first training period will include at least this much data. If not provided,3 * horizon is used.
cutoffs	Cutoffs	list of pd.Timestamp specifying cutoffs to be used during cross validation. If not provided, they are generated as described above.

Examples

Prophet Cross Validator Node Examples

Example 1: Evaluating Forecast Accuracy for Demand

Input Schema:

Time-series data with columns such as “Date” and “Demand”.

Configuration:

Horizon: “30 days” (e.g., evaluating forecasts for the next 30 days).

Period: “15 days” (e.g., cutoffs occur every 15 days).

Initial: “90 days” (e.g., initial training period covers 90 days).

Output:

Metrics such as Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) for each fold of the cross-validation.

Example 2: Cross-Validation for Monthly Revenue Prediction

Input Schema:

Time-series data with columns “Month” and “Revenue”.

Configuration:

Horizon: “3 months”.

Period: “1 month”.

Initial: “12 months”.

Output:

Forecast error metrics aggregated across all cutoff points.