I have a dataset with 4 predictor variables X1, X2, X3, X4, and one response variable Y. I have been asked to check the correlation between these variables and see how they are related and then use a linear model to fit them.
No split of training set: test set is given. I have one data set with 10000 samples. I was planning of splitting this data set in the ratio 80:20 for training and testing respectively.
I'd like to know how to do the same in R programming.
Also in general, we will split it into multiple combinations of training:testing set right? or? Please correct me if am wrong. I am a newbie to ML, so kindly help me out here.