A statistical decision rule with incomplete knowledge about classes

Pattern Recognition

Volumn 26, Issue 1, 1993, Pages 155-165

  Dubuisson, Bernard ^a   Masson, Mylène ^a  

^a UNIVERSITÉ DE TECHNOLOGIE DE COMPIÈGNE   (France)

Author keywords

Classification; Diagnosis; Incomplete knowledge; Incomplete learning set; Rule with reject option

Indexed keywords

DECISION THEORY; EQUIVALENCE CLASSES; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; OPTIMIZATION; PROBABILITY; STATISTICAL METHODS;

BAYES OPTIMAL RULE; CLASSIFICATION; INCOMPLETE KNOWLEDGE; INCOMPLETE LEARNING SET; RULE WITH REJECT OPTION;

PATTERN RECOGNITION;

EID: 0027242497     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/0031-3203(93)90097-G     Document Type: Article

References (18)

1. Results in the application of pattern recognition methods to nuclear component surveillance
2. Machine recognition of abnormal behaviour in nuclear reactor
3. Diagnosis of equipment failure by pattern recognition
4. Surveillance of a nuclear reactor by use of a pattern recognition methodology
5. An optimum character recognition system using decision functions
6. On optimum recognition error and reject tradeoff
7. Decision with reject options
8. The nearest neighbour classification rule with a reject option
9. A generalisation of the kNN rule
10. New error bounds with the nearest neighbour rule
11. Nosing around the neighbourhood: a new system structure and classification rule for recognition in partially exposed environment
12. Computer aided system diagnosis with an incomplete learning set
13. The diagnostic potential of pattern recognition methods applied to temperature noise data from simulated fast reactor fuel sub-assemblies