Exploratory analysis : Regression trees without splitting train-test data I am analyzing a small dataset of 76 observations and I want to explore how 9 environmental predictors explain my response variable. For this I have decided to use regression trees because I am interested to see how the variables interact to each other
I am wondering if its right not to split the data to train & test dataset and just use the entire set to fit the model ?
IMPORTANT : My intention is NOT do use the model for prediction but just for exploration of my current data
I will appreciate any ideas/advice,
A

Part of your exploration should be to test how well a tree can model your data and to do that you should use a train/test split. After you do that you can train your model with the entire dataset (or just training set) for further exploration.
