iaml.actionables.cleaning.act_missing_count_feature¶

[STEP] Add missing value count feature.

Classes¶

ActMissingCountFeature

[STEP] Add missing value count feature.

Module Contents¶

class iaml.actionables.cleaning.act_missing_count_feature.ActMissingCountFeature¶

Bases: iaml.actionable.Actionable

[STEP] Add missing value count feature.

name: str = 'Add missing count feature'¶: Step’s name.

configuration¶: Configuration of this step (equivalent to hyperparameters for models).

columns: list[str] = []¶

feature_name: str | None = None¶

fit(dataset: iaml.dataset.Dataset) → iaml.actionable.Actionable¶

Fits the step on the given dataset.

Parameters:: dataset (Dataset) – Features and labels.
Returns:: Fitted step.

transform(X: pandas.DataFrame) → pandas.DataFrame¶

suitable(dataset: iaml.dataset.Dataset) → bool¶

Evaluates whether the step is suitable to run with the given dataset.

Parameters:: dataset (Dataset) – Dataset to evaluate on.
Returns:: Whether the step is suitable to run.

priorize(candidate: iaml.candidate.Candidate = None) → float¶

Evaluates the priority of the step within a pipeline. 0 means the execution of the step should not be prioritized, and 1 means it should be executed early in the pipeline.

Parameters:: candidate (Candidate, optional) – Candidate on which the priority should be evaluated.
Returns:: Value between 0 and 1.