R, Machine Learning, Nonlinear Regression.
squared error (RMSE) and R-Squared (R2) criteria: 1. Linear Regression Let’s model the relationship between variables with simple linear regression and examine the RMSE and R-squared criteria: model<-lm(medv~lstat,data=train.data) predictions<-model %>% predict(test.data) data.frame(