Feature reduction in multiple linear regression via bivariate correlation coefficients
摘要
This paper explores feature behavior in machine learning models using the Delhi house rent dataset. We analyzed feature relations with a bivariate correlation heatmap and developed two multiple linear regression models trained with different sets of features. Our evaluation included assessing their time complexity and efficiency using various performance metrics. Additionally, we propose that this feature reduction technique could benefit other datasets.