Abstract:
This study focuses on developing a novel strategy for predicting a country's performance in the Olympic Games from 1896 to the present. The approach combines three methods: linear regression, Pearson correlation coefficient, and Spearman correlation coefficient. The primary objective is to compare the values of Spearman and Pearson correlation coefficients for the same dataset. Specifically, the study compares the total number of medals won by each nation with their respective GDP (gross domestic product). By applying these techniques, the project aims to make machine learning-based predictions of Olympic medals. Keywords: Linear Regression, Number of Static Attributes, Pearson Method, Spearman Method (NSF).
This final year engineering project is based on an IEEE Paper and is considered one of the best projects for computer science students. As the best IEEE project center in Bangalore, we provide complete documentation support, fully implemented hardware/software in the students' environment, and organized classes tailored to the project's requirements.