Feature Extraction and Classification Using Ensemble Method to Enhance Parkinson's Disease Prediction-Reference-Cited by-同舟云学术

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Feature Extraction and Classification Using Ensemble Method to Enhance Parkinson's Disease Prediction

Published:2023-11-16 Issue: Volume:6 Page:1-5
ISSN:
Container-title:2023 Annual International Conference on Emerging Research Areas: International Conference on Intelligent Systems (AICERA/ICIS)
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Author:

R Deepa¹,M Sakthivadivel²,S Saravanakumar³,V Ganesh Karthikeyan⁴,M Parimala Devi⁵,S Madumitha⁶

Affiliation:

1. CMR Institute of Technology (VTU University),Department of ECE,Bangalore,India

2. Dr. Mahalingam College of Engineering,Department of CSE,Pollachi,India

3. Jain University,Department of CSE,Bangalore,India

4. Adithya Institute of Technology,Department of IT,Coimbatore,India

5. Velalar College of Engineering and Technology,Department of ECE,Erode,India

6. Sri Sairam College of Engineering,Department of ICE,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10419864/10419874/10420274.pdf?arnumber=10420274

Reference23 articles.

1. Feature Selection and Classification Using CatBoost Method for Improving the Performance of Predicting Parkinson’s Disease

2. Predicting Parkinson’s Disease Progression: Evaluation of Ensemble Methods in Machine Learning

3. A three-stage, deep learning, ensemble approach for prognosis in patients with Parkinson’s disease

4. Breast Cancer Classification using the Supervised Learning Algorithms

5. Parkinson's disease classification using machine learning algorithms: performance analysis and comparison

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