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Arbitrating Among Competing Classifiers Using Learned Referees

https://doi.org/10.1007/pl00011679
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Technical Note: Some Properties of Splitting Criteria
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Boosting and Other Machine Learning Algorithms
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A Comparative Evaluation of Voting and Meta-learning on Partitioned Data
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Distilling Reliable Information From Unreliable Theories
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Simplifying decision trees
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Error Reduction through Learning Multiple Descriptions
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The Strength of Weak Learnability
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A Study of Explanation-Based Methods for Inductive Learning
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A Leisurely Look at the Bootstrap, the Jackknife, and Cross-Validation
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Neural network ensembles
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Adaptive Mixtures of Local Experts
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Hierarchical Mixtures of Experts and the EM Algorithm
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Multivariate Adaptive Regression Splines
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Rerepresenting and Restructuring Domain Theories: A Constructive Induction Approach
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Bias-Driven Revision of Logical Domain Theories
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Learning One More Thing

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