ResidualsOverTime
Residual against date, one marker series per origin, with the zero line.
The residual plot used by regression scatters residuals against the predicted value; forecasting plots them against time, because time is where the error pattern lives. Residuals that drift off zero mean the model is systematically behind or ahead of the series, and a repeating pattern means a missed seasonality.
Methods
compute_forecasts(self, forecasts: Dict[str, Any]) -> List[DashAI.back.core.artifacts.Artifact]
ResidualsOverTimeDraw the zero line and each origin's residuals against the date.
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.