The Role of Linear Discriminant Analysis for Accurate Prediction of Breast Cancer-Reference-Cited by-同舟云学术

The Role of Linear Discriminant Analysis for Accurate Prediction of Breast Cancer

Published:2021-12 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE 14th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)
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Author:

Jessica Egwom Onyinyechi¹,Hamada Mohamed²,Yusuf Saratu Ilu³,Hassan Mohammed³

Affiliation:

1. Bayero University Kano,Department of Computer Science,Kano,Nigeria

2. University of Aizu,Software Eng. Lab,Aizu,Japan

3. Bayero University Kano,Department of Software Eng.,Kano,Nigeria

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9691770/9691932/09691955.pdf?arnumber=9691955

Reference22 articles.

1. Prediction of breast cancer using random forest, support vector machines and naive bayes;elgedawy;International Journal of Computational Engineering Science,2017

2. Mining big data: breast cancer prediction using dt-svm hybrid model;sivakami;International Journal of Scientific Engineering and Applied Science (IJSEAS),2015

3. A neural network recommendation approach for improving accuracy of multi-criteria collaborative filtering;hassan;IEICE Technical Report IEICE Tech Rep,2017

4. Machine Learning with Applications in Breast Cancer Diagnosis and Prognosis

5. Using Machine Learning Algorithms for Breast Cancer Risk Prediction and Diagnosis

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4. Classification of Cervical Cell Images into Healthy or Cancer Using Convolution Neural Network and Linear Discriminant Analysis;2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT);2023-07-13

5. Breast Cancer Prediction Based on Feature Extraction using Hybrid Methodologies;International Journal of Soft Computing and Engineering;2023-05-30