iaml.actionables.predictors.classifier.act_catboost_classifier¶
[STEP] CatBoost
Classes¶
[STEP] CatBoost Classifier |
Module Contents¶
- class iaml.actionables.predictors.classifier.act_catboost_classifier.ActCatBoost¶
Bases:
iaml.predictor.Predictor[STEP] CatBoost Classifier
- name: str = 'CatBoost Classifier'¶
Step’s name.
- refs: list[dict[str, Any]]¶
List of references for this step.
- configuration¶
Configuration of this step (equivalent to hyperparameters for models).
- model: catboost.CatBoostClassifier = None¶
- label_encoder: sklearn.preprocessing.LabelEncoder¶
- passthrough_parameters(default: bool = True) dict[str, Any]¶
Keep CatBoost defaults and omit leaf size for symmetric trees.
- fit(dataset: iaml.dataset.Dataset)¶
Fits the step on the given dataset.
- Parameters:
dataset (Dataset) – Features and labels.
- Returns:
Fitted step.
- property classes_¶
Original labels, in the order of predict_proba columns.
- 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.