I have a dataset with 4 predictor variables $X_1, X_2, X_3, X_4,$ 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 a 80:20 ratio for training and testing respectively.
I would like to know how to do the same in the R programming language.
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 machine learning, so kindly help me out here.