Considering that breast cancer molecular subtypes are naturally imbalanced, with one subgroup of a given subtype, such as more aggressive triple negative (TN) or HER2 positive, being significantly underrepresented than hormone receptor subtypes (ER/PR positive) [20,21,22], we hypothesize that breast cancer in vivo prediction models benefit from data preparation approaches. This evidence concerns the gene PGR and breast carcinoma.