# Direct Strength Method

Machine-learned corrections to global buckling predictions for built-up cold-formed steel columns were previously judged on a random 80/20 split, where specimens from one test programme can sit in both training and test sets. Holding out entire experimental sources instead, across 148 tests from 15 sources and 13 section families, weakens transfer sharply: the best model, Lasso, reaches an $R^2$ of 0.787 and a mean absolute percentage error of 73.0%. Calibrated on those out-of-source predictions, LRFD resistance factors fall to 0.191–0.399 and ASD safety factors to 4.01–8.38.

Machine-learned corrections to global buckling predictions for built-up cold-formed steel columns were previously judged on a random 80/20 split, where specimens from one test programme can sit in both training and test sets. Holding out entire experimental sources instead, across 148 tests from 15 sources and 13 section families, weakens transfer sharply: the best model, Lasso, reaches an $R^2$ of 0.787 and a mean absolute percentage error of 73.0%. Calibrated on those out-of-source predictions, LRFD resistance factors fall to 0.191–0.399 and ASD safety factors to 4.01–8.38.