Augmented Intelligence Helps Improving Human Decision Making Using Decision Tree and Machine Learning

The Progressive approach is used rather than the regular machine learning algorithms in use, analysis works on an athlete’s data set that holds specific columns that are more about the details of athletes. Work explains how an athlete can improve his abilities by analyzing the data of 120 years old Olympic players. Selective details of the athletes have concluded on the feature-based analysis, the main method used is a decision tree and KNN. Those selective features can best explain on what a new athlete need to focus on to secure a medal in Olympics. However, the works remain focused on the technique of machine learning. In analysis the decision tree also performed better, but in overall performance, the best outputs remain with improved KNN. Basic analysis is based on the age and gender of the athletes. However, major analysis based on augmented intelligence concludes the precision, recall, and F1 score. Thus the KNN concluded best results as in F1 Score.