Comparative Study of Dimensionality Reduction Techniques and Machine Learning Algorithms for Alzheimer's Disease Classification and Prediction-Reference-Cited by-同舟云学术

Comparative Study of Dimensionality Reduction Techniques and Machine Learning Algorithms for Alzheimer's Disease Classification and Prediction

Published:2022-12-01 Issue: Volume: Page:
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Container-title:2022 IEEE 3rd International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS)
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Author:

Aouragh Abd Allah¹,Bahaj Mohamed¹,Gherabi Noreddine²

Affiliation:

1. Hassan 1st University,MIET Laboratory Faculty of Sciences and Techniques,Settat,Morocco

2. Sultan Moulay Slimane University,LASTI Laboratory National School of Applied Sciences,Beni-Mellal,Morocco

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9982722/9982807/09983211.pdf?arnumber=9983211

Reference21 articles.

1. A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages

2. Review of classical dimensionality reduction and sample selection methods for large-scale data processing

3. An Improved Multi-Modal based Machine Learning Approach for the Prognosis of Alzheimer's disease;khan;Journal of King Saud University - Computer and Information Sciences,2020

4. PCA based feature reduction to improve the accuracy of decision tree c4.5 classification

5. Overview and comparative study of dimensionality reduction techniques for high dimensional data

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