Breast cancer classification using snapshot ensemble deep learning model and t-distributed stochastic neighbor embedding
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-022-13419-5.pdf
Reference42 articles.
1. Abdar M, Makarenkov V (2019)CWV-BANN-SVM ensemble learning classifier for an accurate diagnosis of breast cancer. Measurement 146:557–570
2. Abdar M, Makarenkov V (2019)CWV-BANN-SVM ensemble learning classifier for an accurate diagnosis of breast cancer. Measurement. https://doi.org/10.1016/j.measurement.2019.05.022
3. Ahmad LG, Eshlaghy AT, Poorebrahimi A, Ebrahimi M, Razavi AR (2013) Using three machine learning techniques for predicting breast cancer recurrence. J Health Med Inform 4:124. https://doi.org/10.4172/2157-7420.1000124
4. Alam KMR, Siddique N, Adeli H (2020) A dynamic ensemble learning algorithm for neural networks. Neural Comput Appl 32(12):8675–8690. https://doi.org/10.1007/s00521-019-04359-7
5. Alam KM, Siddique N, Adeli H (2020) A dynamic ensemble learning algorithm for neural networks. Neural Comput Appl 8675–8690. https://doi.org/10.1007/s00521-019-04359-7
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