How are feature_importances in RandomForestClassifier determined?

Question

I have a classification task with a time-series as the data input, where each attribute (n=23) represents a specific point in time. Besides the absolute classification resul

Answer 1

It's the ratio between the number of samples routed to a decision node involving that feature in any of the trees of the ensemble over the total number of samples in the training set.

Features that are involved in the top level nodes of the decision trees tend to see more samples hence are likely to have more importance.

Edit: this description is only partially correct: Gilles and Peter's answers are the correct answer.