Abstract | ||
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In order to rank the performance of machine learning algorithms, many researchers conduct experiments on benchmark data sets. Since most learning algorithms have domain-specific parameters, it is a popular custom to adapt these parameters to obtain a ... |
Year | Venue | Keywords |
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1997 | IJCAI | bayesian approach,fixed example size,benchmark data set,popular custom,domain-specific parameter |
Field | DocType | ISSN |
Variable-order Bayesian network,Computer science,Artificial intelligence,Machine learning,Bayesian probability | Conference | 1045-0823 |
ISBN | Citations | PageRank |
1-555860-480-4 | 11 | 0.84 |
References | Authors | |
5 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Eric McCreath | 1 | 132 | 14.64 |
Arun Sharma | 2 | 215 | 17.14 |