ForecastVsActual
The actual series and every origin's forecast, against the dates.
An error scalar says how far off the forecasts are on average; this says where. A forecast that tracks well early in its window and drifts later shows an error that compounds over the horizon, a line that runs parallel but offset shows a level bias, and an actual value outside the shaded 95% interval shows a model more confident than it had reason to be.
Methods
compute_forecasts(self, forecasts: Dict[str, Any]) -> List[DashAI.back.core.artifacts.Artifact]
ForecastVsActualDraw the actual series, then each origin's forecast and band.
Returns
- List[Artifact]
- One figure: the actual values over every forecast date, and per origin its forecast with its 95% interval shaded when it has one.
compute(self, y_true, y_pred, class_names: Optional[List[str]] = None) -> List[DashAI.back.core.artifacts.Artifact]
ForecastingReportA forecasting report has no rows to draw: see compute_forecasts.
get_credential(self, name: str)
ConfigObjectResolve a registered credential component by name.
Parameters
- name : str
- Credential component class name (e.g. "HuggingFaceCredential").
Returns
- BaseCredential
- An instance of the requested credential component.
get_metadata(cls) -> Dict[str, Any]
BaseReportGet metadata values for the current report.
Returns
- Dict[str, Any]
- UI metadata, including whether the report needs a model that outputs class probabilities.
get_schema(cls) -> dict
ConfigObjectGenerates the component related Json Schema.
Returns
- dict
- Dictionary representing the Json Schema of the component.
validate_and_transform(self, raw_data: dict) -> dict
ConfigObjectIt takes the data given by the user to initialize the model and returns it with all the objects that the model needs to work.
Parameters
- raw_data : dict
- A dictionary with the data provided by the user to initialize the model.
Returns
- dict
- A validated dictionary with the necessary objects.