Optimal Sample Size for the Birnbaum-Saunders Distribution under Decision Theory with Symmetric and Asymmetric Loss Functions.
Eliardo CostaManoel Santos-NetoVíctor LeivaPublished in: Symmetry (2021)
Keyphrases
- sample size
- loss function
- decision theory
- worst case
- utility function
- model selection
- loss minimization
- learning to rank
- pairwise
- risk minimization
- random sampling
- decision theoretic
- support vector
- decision making
- upper bound
- generalization error
- pac learning
- artificial intelligence
- reproducing kernel hilbert space
- progressive sampling
- covariance matrix
- game theory
- optimal solution
- case based reasoning
- np hard
- semi supervised
- probability distribution
- vc dimension
- evolutionary algorithm
- machine learning
- data sets