Journal article Open Access

Enhanced Optimal Feature Selection Techniques for Parkinson's disease Detection using Machine Learning Algorithms

J. Jayashree; G. Maheswar Reddy; M. Sai Pradyumna Reddy; M. Sai Balaram Reddy; J. Vijayashree

Sponsor(s)
Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP)

Parkinson disease is a common mass measurement problem in public health. Machine-based learning is used to differentiate between the stable and Parkinson's disease people. This paper provides a comprehensive review of the Parkinson disease buying estimate using machine-based learning approaches. A brief introduction is given to various methods of artificial intelligence, focused on strategies used to predict Parkinson disease. This paper also offers a study of the results obtained by using MRMR feature selection algorithms with four classifications for Parkinson’s disease detection using python

Files (921.3 kB)
Name Size
C6628029320.pdf
md5:197b6e89120b2e6a0d82a5cfa9a6ce8d
921.3 kB Download
24
10
views
downloads
All versions This version
Views 2424
Downloads 1010
Data volume 9.2 MB9.2 MB
Unique views 2323
Unique downloads 1010

Share

Cite as