I have a matrix of 358.367 data. Each row is a DNA sequence from the human genome. I want to build a classification model in R, using XGBoost algorithm and 83 features (dinucleotides, trinucleotides, etc.).
How should I split the data for the train and test set?
For example 70% for the train set and 30% for the test set? 30% for the train set and 70% for the test set?