RegressionTask

Task

DashAI.back.tasks.RegressionTask

Abstract base task for continuous-output (regression) problems in DashAI.

Regression tasks predict one or more continuous numeric values from input features. This base class constrains output columns to Float or Integer types and accepts Float, Integer, and Categorical input types. Unlike classification tasks, regression does not require a Categorical output and num_labels always returns None.

Methods

num_labels(self, dataset: 'DashAIDataset', output_column: str) -> int | None

Defined on RegressionTask

Get the number of unique labels in the output column.

Parameters

dataset : DashAIDataset: Dataset used for training
output_column : str: Output column

Returns

int | None: Number of unique labels or None if not applicable

prepare_for_task(self, dataset: Union[ForwardRef('DatasetDict'), ForwardRef('DashAIDataset')], input_columns: List[str], output_columns: List[str]) -> 'DashAIDataset'

Defined on RegressionTask

Convert the dataset to DashAIDataset and validate types.

Parameters

datasetdict : DatasetDict: Dataset to be changed

Returns

DashAIDataset: Dataset with validated types

process_predictions(self, dataset: 'DashAIDataset', predictions: 'ndarray', output_column: str)

Defined on RegressionTask

Process the predictions

Parameters

dataset : DashAIDataset: Dataset used for training
predictions : np.ndarray: Predictions from the model
output_column : str: Output column

Returns

Processed predictions

get_metadata(cls) -> Dict[str, Any]

Defined on BaseTask

Return serialisable metadata for the current task.

Parameters

cls : type: The task class (injected automatically by Python for classmethods).

Returns

Dict[str, Any]: Dictionary with keys "inputs_types", "outputs_types", "inputs_cardinality", and "outputs_cardinality".

process_manual_input(self, manual_input: List[dict], dataset_path: str) -> 'DashAIDataset'

Defined on BaseTask

Process manual input data into a DashAIDataset with type validation.

Parameters

manual_input : List[dict]: List of dictionaries representing manual input data.
dataset_path : str: Path to the training dataset (used to get column specs for validation)

Returns

DashAIDataset: Processed DashAIDataset from manual input.

validate_dataset_for_task(self, dataset: 'DashAIDataset', dataset_name: str, input_columns: List[str], output_columns: List[str]) -> None

Defined on BaseTask

Validate a dataset for the current task.

Parameters

dataset : DashAIDataset: Dataset to be validated
dataset_name : str: Dataset name

Methods​

Methods