- class miml.classifier.miml_classifier.MIMLClassifier#
Bases:
ABC
Class to represent a MIMLClassifier
- abstract evaluate(dataset_test: MIMLDataset) ndarray #
Evaluate the model on a test dataset
Parameters#
- dataset_testMIMLDataset
Test dataset to evaluate the model on.
Returns#
- resultsndarray of shape (n_bags, n_labels)
Predicted labels of dataset_test
- fit(dataset_train: MIMLDataset) None #
Training the classifier
Parameters#
- dataset_trainMIMLDataset
Dataset to train the classifier
- abstract fit_internal(dataset_train: MIMLDataset) None #
Internal method to train the classifier
Parameters#
- dataset_trainMIMLDataset
Dataset to train the classifier
- abstract predict(x: ndarray) ndarray #
Predict labels of given data
- xndarray of shape (n, n_labels)
Data to predict their labels
Returns#
- resultsndarray of shape (n_bags, n_labels)
Predicted labels of data
- abstract predict_bag(bag: Bag) ndarray #
Predict labels of a given bag
Parameters#
- bagBag
Bag to predict their labels
Returns#
- resultsndarray of shape (n_bags, n_labels)
Predicted labels of the bag
- abstract predict_proba(dataset_test: MIMLDataset) ndarray #
Predict probabilities of given dataset of having a positive label
Parameters#
- dataset_testMIMLDataset
Dataset to predict probabilities
Returns#
- results: np.ndarray of shape (n_instances, n_features)
Predicted probabilities for given dataset