I have a dataset with 10 columns and 158 rows. I try to predict my test dataset which is 1 columns with 158 rows.
I made cross-validations, grid-search and use ElasticNet algorithm.
Also before the evaluate the model I check the pearson correlation between 10 columns which I used for train with other 1 column which I try to predict. The correlation is not good but when I evaluate model the R^2 score is near 0.98 .
How can I be ensure that this score is confidental ? Because I didn't expect a R^2 like this. This is too high that I expect.
Thanks in advance.