I have a dataset of 93 records and 45 radiomics variables from various CT scans. I wanted to check if age and sex could be classified by the variables so I made a new variable with both sex and age. I tried various approaches (PCA, ICA and VIF for feature selection and recursive partitioning for classification, plus elastic net for selection and classification). I am now evaluating the performance of my models, but I have a doubt. Should I perform feature selection on the whole dataset or only on the train data?