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ForecastFutureUnit

Unit
DashAI.back.units.ForecastFutureUnit

Forecast the steps of the future rows, reading their exogenous values.

The sibling of ForecastHorizonUnit for a run that read exogenous variables, and a provisional one: the contract cannot declare an optional input yet (ATOMIZING §5.4), and once it can this folds into that unit with an optional x_future (RECONCILING_FORECASTING §7.2, decision 2). The two share the helpers that forecast and check the grid.

dataset holds the future rows PrepareFutureUnit checked, one per step, and model_input the same rows after the session's final.pkl. The horizon is their number, and the model reads, from model_input, the columns it was fitted on. The forecast is published as y_pred, and dataset goes on unchanged: the saved prediction keeps the exogenous values it was made with.

Parameters​

exogenous_columns : array, default=[]
The exogenous columns the model reads, as the session's preprocessing resolved them for the final fit.

Methods​

execute(self, ctx: DashAI.back.units.context.ExecutionContext) -> None

Defined on ForecastFutureUnit

Do the unit's work, reading from and writing to the context.

Parameters

ctx : ExecutionContext
The shared execution context.

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_schema(cls) -> dict

Defined on ConfigObject

Generates the component related Json Schema.

Returns

dict
Dictionary representing the Json Schema of the component.

validate(self, ctx: DashAI.back.units.context.ExecutionContext) -> None

Defined on BaseUnit

Check preconditions without executing the unit.

Parameters

ctx : ExecutionContext
The shared execution context.

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.