Handling Imbalanced Data in Road Crash Severity Prediction by Machine Learning Algorithms

Crash severity is undoubtedly a fundamental aspect of a crash event. Although machine learning algorithms for predicting crash severity have recently gained interest by the academic community, there is a significant trend towards neglecting the fact that crash datasets are acutely imbalanced. Overlo...

Full description

Saved in:

Bibliographic Details
Published in:	Infrastructures (Basel) Vol. 5; no. 7; p. 61
Main Authors:	Fiorentini, Nicholas, Losa, Massimo
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 20.07.2020
Subjects:	Algorithms Classification Classifiers crash severity Crashes Datasets Decision making Decision trees k-nearest neighbor Machine learning machine learning classification algorithms Neural networks Performance evaluation Prediction models Property damage random classification tree random forest random undersampling the majority class Regression Roads & highways Studies
ISSN:	2412-3811, 2412-3811
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!