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This project is based on a dataset, which is composed of a range of biomedical voice measurements from 31 people, 23 with Parkinson's disease (PD). Each column in the table is a particular voice measure, and each row corresponds to one of 195 voice recordings from these individuals ("name" column).
The objective of the project is to discriminate healthy people from those with PD, according to the "status" column which is set to 0 for healthy and 1 for PD.
The dataset is in ASCII CSV format. The rows of the CSV file contain an
instance corresponding to one voice recording.
This video focuses on Machine Learning Algorithms: Logistic Regression. Please ask your queries in the comment box. This video covers how ML techniques as Decision Tree, Random Forest, SVM, KNN are applied. It also find out training and tests prediction accuracy for all the techniques, to find out the best among them.
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