Blender

class lightautoml.automl.blend.Blender[source]

Bases: object

Basic class for blending.

Blender learns how to make blend on sequence of prediction datasets and prune pipes, that are not used in final blend.

fit_predict(predictions, pipes)[source]

Wraps custom ._fit_predict methods of blenders.

Method wraps individual ._fit_predict method of blenders. If input is single model - take it, else ._fit_predict Note - some pipelines may have more than 1 model. So corresponding prediction dataset have multiple prediction cols.

Parameters

predictions (Sequence[LAMLDataset]) – Sequence of datasets with predictions.
pipes (Sequence[MLPipeline]) – Sequence of pipelines.

Return type

Tuple[LAMLDataset, Sequence[MLPipeline]]

Returns

Single prediction dataset and sequence of pruned pipelines.

predict(predictions)[source]

Wraps custom ._fit_predict methods of blenders.

Parameters: predictions (Sequence[LAMLDataset]) – Sequence of predictions from pruned datasets.
Return type: LAMLDataset
Returns: Dataset with predictions.

split_models(predictions)[source]

Split predictions by single model prediction datasets.

Parameters: predictions (Sequence[LAMLDataset]) – Sequence of datasets with predictions.
Return type: Tuple[Sequence[LAMLDataset], List[int], List[int]]
Returns: Split predictions, model indices, pipe indices.

score(dataset)[source]

Score metric for blender.

Parameters: dataset (LAMLDataset) – Blended predictions dataset.
Return type: float
Returns: Metric value.