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ResidualAutocorrelation

Report
DashAI.back.reports.forecasting.ResidualAutocorrelation

Autocorrelation of the residuals against the number of lags.

A good forecast leaves residuals that look like noise: each error carries no information about the next. Autocorrelation measures exactly that, so a bar above the confidence band means the model left structure behind — neighbouring periods are wrong in the same direction, which a tuned model would have learned. Lags rising and falling smoothly usually mean a missed trend or seasonality, while a single spike means a specific lag that was never modelled.

Parameters

max_lag : integer, default=20
Number of lags to plot the autocorrelation for.

Methods

compute(self, y_true, y_pred, class_names: Optional[List[str]] = None) -> List[DashAI.back.core.artifacts.Artifact]

Defined on ResidualAutocorrelation

Build the residual autocorrelation bar chart.

Parameters

y_true : ndarray
Ground truth values of the series.
y_pred : ndarray
The model's forecast for the same points.
class_names : Optional[List[str]]
Unused; always None for forecasting.

Returns

List[Artifact]
A single bar figure with a confidence band around zero.

get_credential(self, name: str)

Defined on ConfigObject

Resolve 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]

Defined on BaseReport

Get 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

Defined on ConfigObject

Generates the component related Json Schema.

Returns

dict
Dictionary representing the Json Schema of the component.

validate_and_transform(self, raw_data: dict) -> dict

Defined on ConfigObject

It 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.

Compatible with