Statements (22)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:mathematical_concept
|
| gptkbp:alternativeName |
No Free Lunch theorem for optimization
No Free Lunch theorem for search |
| gptkbp:appliesTo |
supervised learning
search problems black-box optimization |
| gptkbp:author |
gptkb:William_G._Macready
gptkb:David_H._Wolpert |
| gptkbp:citation |
gptkb:IEEE_Transactions_on_Evolutionary_Computation
|
| gptkbp:field |
gptkb:machine_learning
optimization search algorithms |
| gptkbp:fullName |
No Free Lunch theorem
|
| https://www.w3.org/2000/01/rdf-schema#label |
NFL theorem
|
| gptkbp:impact |
influences understanding of algorithm performance limits
|
| gptkbp:publicationYear |
1997
|
| gptkbp:relatedTo |
bias-variance tradeoff
inductive bias algorithm selection |
| gptkbp:sentence |
No optimization algorithm is universally better than any other when performance is averaged across all possible problems.
|
| gptkbp:bfsParent |
gptkb:No_Free_Lunch_Theorem
|
| gptkbp:bfsLayer |
7
|