rocelib.models.sklearn_models package
Submodules
rocelib.models.sklearn_models.TrainableDecisionTreeModel module
- class rocelib.models.sklearn_models.TrainableDecisionTreeModel.TrainableDecisionTreeModel[source]
Bases:
TrainableSKLearnModel
A Decision Tree Classifier model wrapper for scikit-learn.
Inherits from TrainableSKLearnModel and initializes a DecisionTreeClassifier as the underlying model.
rocelib.models.sklearn_models.TrainableLogisticRegressionModel module
- class rocelib.models.sklearn_models.TrainableLogisticRegressionModel.TrainableLogisticRegressionModel[source]
Bases:
TrainableSKLearnModel
A Logistic Regression Classifier model wrapper for scikit-learn.
Inherits from TrainableSKLearnModel and initializes LogisticRegression as the underlying model.
rocelib.models.sklearn_models.TrainableSVMModel module
- class rocelib.models.sklearn_models.TrainableSVMModel.TrainableSVMModel[source]
Bases:
TrainableSKLearnModel
A SVM model wrapper for scikit-learn.
Inherits from TrainableSKLearnModel and initializes SVC as the underlying model.
rocelib.models.sklearn_models.TrainableSKLearnModel module
- class rocelib.models.sklearn_models.TrainableSKLearnModel.TrainableSKLearnModel(model)[source]
Bases:
TrainableModel
A base class for scikit-learn models.
This class wraps a scikit-learn model and provides methods for training, predicting, and evaluating the model. Inherits from TrainableModel.
- evaluate(X, y)[source]
Evaluates the model’s performance using accuracy and F1 score.
@param X: The feature variables, should be a DataFrame. @param y: The true target values, should be a DataFrame. @return: A dictionary with “accuracy” and “f1_score” of the model.
- Return type:
dict
- predict(X)[source]
Predicts the outcomes for given feature variables.
@param X: The feature variables, should be a DataFrame. @return: Predictions for each instance, returned as a DataFrame.
- Return type:
DataFrame
- predict_proba(X)[source]
Predicts the probabilities of outcomes for given feature variables.
@param X: The feature variables, should be a DataFrame. @return: Probabilities of each outcome, returned as a DataFrame.
- Return type:
DataFrame
- predict_proba_tensor(X)[source]
Predicts the probabilities of outcomes for given feature variables.
@param X: The feature variables, should be a DataFrame. @return: Probabilities of each outcome, returned as a DataFrame.
- Return type:
Tensor