Mila wishes to build a machine learning model to classify PET images as either containing cancerous tumours, or not. Mila performs the following steps:

·        First, she splits her data into training/test sets.

·        Next, Mila creates 100 subsets of her training data by resampling images from the training data, with replacement, until each dataset contains 200 images.

·        Then, she trains 100 models (one for each subset, and each model is a logistic regression) 

·        Finally, Mila runs each of the 100 models through the test set, and uses as her final prediction for each test image the majority vote of the 100 models.

Mila’s experiment is an example of the ensemble method known as: