Linear Mode Connectivity

"Linear Mode Connectivity" refers to the relationship between input variables and output variables in a linear regression model. By combining input variables through weights to predict the output variable, understanding this connectivity helps in interpreting model results and identifying the most important input variables for predicting the output variable. This has significant application value in model optimization and feature selection.