as the hyperparameter tuple whose low rank model produces the lowest approximation error over The deployment low rank model is then a new low rank model (a) with hyperparameter tuple (k (θ) opt , λ (θ) opt ) and (b) trained on all [simulated] observed entries (train + validation data) of A (θ) . We evaluate the performance of the deployment model by comparing its predictions of the missing entries to the actual values of the missing entries that comprise the test data. N.b., the loss and performance evaluation is done on the standardized and, in the case of Henry coefficients, log 10 -transformed values.