Cost-Sensitive Learning based on Performance Metric for Imbalanced Data
Author:
Funder
CAPES
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software
Link
https://link.springer.com/content/pdf/10.1007/s11063-022-10756-2.pdf
Reference61 articles.
1. Castro CL, Braga AP (2013) Novel cost-sensitive approach to improve the multilayer perceptron performance on imbalanced data. IEEE Trans Neural Netw Learn Syst 24(6):888
2. Aurelio YS, Almeida GM, Castro CL, Braga AP (2019) Learning from imbalanced data sets with weighted cross-entropy function. Neural Process Lett 50:1937
3. Haixiang G, Yijing L, Shang J, Mingyun G, Yuanyue H, Bing G (2017) Learning from class-imbalanced data: review of methods and applications. Expert Syst Appl 73(1):220
4. Lan J, Hu MY, Patuwo E, Zhang GP (2010) An investigation of neural network classifiers with unequal misclassification costs and group sizes. Decis Support Syst 48(4):582
5. Thai-Nghe N, Gantner Z, Schmidt-Thieme L (2010) Cost-sensitive learning methods for imbalanced data, in Proc. International Joint Conference on Neural Networks (IEEE, 2010), pp. 1–8
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