Some Theory For Practical Classifier Validation

Eric Bax; Ya Le

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arXiv · 1510.02676

Some Theory For Practical Classifier Validation

Eric Bax·Ya Le

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Abstract

We compare and contrast two approaches to validating a trained classifier while using all in-sample data for training. One is simultaneous validation over an organized set of hypotheses (SVOOSH), the well-known method that began with VC theory. The other is withhold and gap (WAG). WAG withholds a validation set, trains a holdout classifier on the remaining data, uses the validation data to validate that classifier, then adds the rate of disagreement between the holdout classifier and one trained using all in-sample data, which is an upper bound on the difference in error rates. We show that complex hypothesis classes and limited training data can make WAG a favorable alternative.

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Eric Bax, Ya Le. 2015-10-09. Some Theory For Practical Classifier Validation. https://arxiv.org/abs/1510.02676

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