iaml.actionables.imbalance.act_smote

[STEP] SMOTE

Classes

ActSMOTE

[STEP] SMOTE

Module Contents

class iaml.actionables.imbalance.act_smote.ActSMOTE

Bases: iaml.actionable.Actionable

[STEP] SMOTE

name: str = 'SMOTE'

Step’s name.

refs: list[dict[str, Any]]

List of references for this step.

configuration

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

resampler: imblearn.over_sampling.SMOTE | imblearn.over_sampling.SMOTENC | None = None

categorical_columns: list[str] = []

categorical_indices: list[int] = []

numeric_columns: list[str] = []

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

Fits the step on the given dataset.

Parameters:

dataset (Dataset) – Features and labels.

Returns:

Fitted step.

resample(X: pandas.DataFrame, y: pandas.DataFrame) → tuple[pandas.DataFrame, pandas.DataFrame]

Apply SMOTE.

Parameters:

• X (pd.DataFrame) – Features to resample

• y (pd.DataFrame) – Labels to resample

Returns:

Resampled X and y

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.

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.