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0111 · May 201919922001200920172026
2 results for mutation-validation

Study compares mutation validation and cross-validation for model selection.

problem Comparing model selection methods for generalization performance and computational efficiency.
method Empirical comparison using benchmark and real-world datasets with Bayesian tests.
result Both methods select models with equivalent generalization performance but MV selects simpler models and is computationally cheaper.

We introduce an exploratory study on Mutation Validation (MV), a model validation method using mutated training labels for supervised learning. MV mutates training data labels, retrains the model against the mutated data, then uses the metamorphic relation that captures the consequent training performance changes to as…

2019-05-24abs ↗pdf ↗