Evaluation of Different Heuristics for Accommodating Asymmetric Loss Functions in Regression.
Andrei TolstikovFrederik JanssenJohannes FürnkranzPublished in: DS (2017)
Keyphrases
- loss function
- reproducing kernel hilbert space
- support vector
- gradient boosting
- empirical risk
- pairwise
- squared error
- loss minimization
- logistic regression
- square loss
- risk minimization
- learning to rank
- linear regression
- regression model
- objective function
- hinge loss
- least squares
- convex loss functions
- aggregating algorithm
- boosting algorithms
- model selection