Let's consider a scenario where researchers are working on developing an automated system to classify images of a rare medical condition. Due to the limited number of patients affected by this condition our training data consists of a few hundred images. However, when they go to run the model, it overfits the training data. What is the BEST reason that the model is overfitting the training data? The model is too complex relative to the data The quantity of the training data is too smallThe training data is too "noisy"