Figure 5.

Tree representation of the classification process performed by the decision tree model on the training dataset. At each branch, a decision was made based on the feature printed to classify the dataset into class 0 (did not leave) or class 1 (did leave). The model used Contraction_time and then Cilia to classify the whole training dataset in two steps. Each box represents a group being classified, showing the class predicted, the probability of a correct prediction and the size of the group as a percentage of the whole training dataset (e.g. in box 2, the probability of an organism in this group belonging to class 0 is 0.88, and the group contains 24% of the whole training dataset). (Online version in colour.)