Above are papers related to the following paper: [Paper_ID] Paper #29738. 	[Title] An Optimum Decision Rule for Pattern Recognition [Abstract]  Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #155277. 	[Title] On Functional Relation between Recognition Error and Class-Selective Reject [Abstract] This report reviews various optimum decision rules for pattern recognition, namely, Bayes rule, Chow's rule (optimum error-reject tradeoff), and a recently proposed class-selective rejection rule. The latter provides an optimum tradeoff between the error rate and the average number of (selected) classes. A new general relation between the error rate and the average number of classes is presented. The error rate can directly be computed from the class-selective reject function, which in turn can be estimated from unlabelled patterns, by simply counting the rejects. Theoretical as well as practical implications are discussed and some future research directions are proposed. Please summarise all the given information.

Paper #29738 has the title `An Optimum Decision Rule for Pattern Recognition  
` and the abstract ` 
`.
Question: Which category should Paper #29738 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].


Paper #29738 has the title `An Optimum Decision Rule for Pattern Recognition  
` and the abstract ` 
`.
Question: Which category should Paper #29738 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].

This paper should be classified into: Probabilistic_Methods