Automatically Finding the Biggest Fold Value for More Accurate Classification and Diagnosis in Machine Learning Algorithms-Reference-Cited by-同舟云学术

Automatically Finding the Biggest Fold Value for More Accurate Classification and Diagnosis in Machine Learning Algorithms

Published:2023-12-18 Issue: Volume: Page:
ISSN:2228-6179
Container-title:Iranian Journal of Science and Technology, Transactions of Electrical Engineering
language:en
Short-container-title:Iran J Sci Technol Trans Electr Eng

Author:

Avuçlu Emre

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Computer Vision and Pattern Recognition,Energy Engineering and Power Technology,Signal Processing

Link

https://link.springer.com/content/pdf/10.1007/s40998-023-00682-x.pdf

Reference54 articles.

1. Al-Hyari AY, Al-Taee AM, Al-Taee MA (2013) Clinical decision support system for diagnosis and management of chronic renal failure. In: 2013 IEEE Jordan conference on applied electrical engineering and computing technologies (AEECT). IEEE

2. Arı E, Yıldız Z (2013) Parallel lines assumption in ordinal logistic regression and analysis approaches. Int Interdiscip J Sci Res 1(3):8–23

3. Asri H, Mousannif H, Moatassime HA, Noel T (2016) Using machine learning algorithms for breast cancer risk prediction and diagnosis. Procedia Comput Sci 83:1064–1069. https://doi.org/10.1016/J.Procs.2016.04.224

4. Avuçlu E (2021) A new data augmentation method to use in machine learning algorithms using statistical measurements. Measurement 180:109577. https://doi.org/10.1016/j.measurement.2021.109577

5. Bhooshan N, Giger M, Medved M, Li H, Wood A, Yuan Y, Lan L, Marquez A, Karczmar G, Newstead G (2014) Potential of computer-aided diagnosis of high spectral and spatial resolution (Hiss) MRI in the classification of breast lesions. J Magn Reson Imaging 39(1):59–67