Predicting Risk of Delays in Postal Deliveries with Neural Networks and Gradient Boosting Machines
This thesis conducts a study on a data set from the Swedish and Danish postal service Postnord, comparing an artificial neural network (ANN) and a gradient boosting machine (GBM) for predicting delays in package deliveries. The models are evaluated based on F1-score for the important class which rep...
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Format: | Others |
Language: | English |
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Linköpings universitet, Institutionen för datavetenskap
2020
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Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-169478 |