Pruning SMAC search space based on key hyperparameters.
Hui LiQingqing LiangMei ChenZhenyu DaiHuanjun LiMing ZhuPublished in: Concurr. Comput. Pract. Exp. (2022)
Keyphrases
- search space
- hyperparameters
- model selection
- cross validation
- effective pruning
- bayesian inference
- bayesian framework
- closed form
- support vector
- search algorithm
- gaussian process
- random sampling
- gaussian processes
- maximum likelihood
- maximum a posteriori
- prior information
- parameter space
- fitness function
- incremental learning
- optimal solution
- noise level
- missing values
- marginal likelihood
- sample size
- em algorithm
- state space
- data mining
- incomplete data
- error rate
- denoising
- decision trees