/Parkinson-disease-ML-classifier-

The research-based project where we created a program that gave us the basic initiation on which classification algorithm would be best for prediction of Parkinson's disease using dataset available on UCI ML repository.

Primary LanguageJupyter Notebook

Parkinson-disease-ML-classifier-

Parkinson's disease is a brain disorder that causes unintended or uncontrollable movements, such as shaking, stiffness, and difficulty with balance and coordination. The research-based project where our goal was to create a program that gave us the basic initiation on which model would be the best choice for prediction of Parkinson’s disease. We took data from UCI machine learning repository which consists of 22 vocal parameters of 195 patients. The ‘status’ column is a binary classification of whether the person of a certain vocal parameter has Parkinson disease or not. We used seven different classification algorithms and calculated different performance analysis tests and concluding SVC with near perfect score.

TO RUN PROGRAM:

  1. Download anoconda
  2. Install XGBOOST and Gradio library
  3. Run program on jupyter notebook