Statistical learning theory
From Wikipedia, the free encyclopedia
Statistical learning theory is an ambiguous term.
- It may refer to computational learning theory, which is a sub-field of theoretical computer science that studies how algorithms can learn from data.
- It may refer to Vapnik-Chervonenkis theory, which is a specific approach to computational learning theory, proposed by Vladimir Vapnik and Alexey Chervonenkis.
 |
This disambiguation page lists articles associated with the same title. If an internal link led you here, you may wish to change the link to point directly to the intended article. |
