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Predicting the probability distribution of bus travel time to move towards reliable planning of public transport services
Two types of probabilistic models, namely similarity-based density estimation models and a smoothed Logistic Regression for probabilistic classification model, are compared on a dataset of more than 41, 000 trips and 50 bus routes of the city of Montr\'eal.
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