PREDICTING PARKINSON’S DISEASE using XGBOOST ALGORITHM. In this project we will be using python to
build a model using which we can accurately detect the presence of Parkinson’s disease in one’s body. XGBOOST algorithm is a technique for regression and classification problems. It produces a prediction model in form of a decision tree. Data is loaded, features and label are specified, data is split, XGBClassifier is produced and calculate the accuracy of our model.