Machine Learning Methods with Decision Forests for Parkinson’s Detection

• Published in: Applied sciences Vol. 11; no. 2; p. 581
• Main Authors: Pramanik, Moumita, Pradhan, Ratika, Nandy, Parvati, Bhoi, Akash Kumar, Barsocchi, Paolo
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.01.2021
• Subjects: Accuracy; Acoustics; Algorithms; Classification; decision forest comparison; decision tree ensemble; Decision trees; ForestPA; Gene expression; Input output; Machine learning; Neural networks; Parkinson detection; SysFor; training-testing split; Wavelet transforms

Biomedical engineers prefer decision forests over traditional decision trees to design state-of-the-art Parkinson’s Detection Systems (PDS) on massive acoustic signal data. However, the challenges that the researchers are facing with decision forests is identifying the minimum number of decision tre...