A Prediction Combination for Covariates Available before Action
Abstract
An ordinal combination is useful for covariate-indexed selection only if it preserves the comparisons changing the decision. Evaluation should retain separate-model recommendations before combining them and independently check their consequential reversals. Covariates must be available at the action time. Numerical average fit does not establish an implementable or well-covered contextual rule. This focused synthesis develops an empirical comparison that preserves the terminal action, observation process, and total verification cost. Its proposed tests are prospective; no new simulation run, model-training result, or intervention effect is reported.
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