Multi-Objective Approximation for the Optimal Design of Control Charts with Variable Parameters using the Taguchi Loss Function.
Oscar Oviedo-TrespalaciosRita Peñabaena-NieblesPublished in: CoDIT (2019)
Keyphrases
- loss function
- optimal design
- multi objective
- pairwise
- control charts
- support vector
- evolutionary algorithm
- bayes rule
- statistical process control
- logistic regression
- learning to rank
- multi objective optimization
- optimization algorithm
- maximum likelihood
- regularization term
- risk minimization
- empirical risk
- real time
- weight vector
- reproducing kernel hilbert space
- objective function
- parameter selection
- precision and recall
- learning rate
- stochastic gradient descent
- optimization problems
- genetic algorithm