I am working on a project with a sample size of 30. I have 7 features predicting a continuous variable where I am aiming to optimize the r-value. If I change the random seed of my train_test_split() 100 times, I get correlation coefficients that range between .6 and .9 with an occasional negative r-value.
How should I interpret this? Is this variability normal for such a small data set and a random shuffling of my training data? Or is something else going on? How should I decided which seed to use?