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

descriptionPublicationkeyboard_double_arrow_right Article 28 Feb 2020Publisher:Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESPJournal:International Journal of Engineering and Advanced Technology, volume 9, pages 4,375-4,384 (eissn: 2249-8958,

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

doi: 10.35940/ijeat.c6628.029320 , 10.5281/zenodo.5596057 , 10.5281/zenodo.5596056

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

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Abstract

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

Keywords

Parkinson Disease(PD), Types of Parkinson's Disease, Stages, Symptoms, Causes, Risk Factor, Complications, Treatment, Prevention, Statistics, MRMR ,python., C6628029320/2020��BEIESP, 2249-8958

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