Predicting Risk of Delays in Postal Deliveries with Neural Networks and Gradient Boosting Machines

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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Bibliographic Details
Main Author: Söderholm, Matilda
Format: Others
Language:English
Published: Linköpings universitet, Institutionen för datavetenskap 2020
Subjects:
Machine Learning
Artificial Neural Networks
Gradient Boosting
Delivery prediction
Delay prediction
Postal Deliveries
Computer and Information Sciences
Data- och informationsvetenskap
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-169478

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-169478

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