Open AccessEnhanced Optimal Feature Selection Techniques for Parkinson’s disease Detection using Machine Learning Algorithms
Author(s) -
J Jayashree,
G. Maheswar Reddy,
M. Sai Pradyumna Reddy,
M. Sai Balaram Reddy,
J. Vijayashree
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.c6628.029320
Subject(s) - feature selection , machine learning , parkinson's disease , artificial intelligence , computer science , disease , python (programming language) , algorithm , medicine , pathology , operating system
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