Parameter Sensitivity Analysis for the Progressive Sampling-Based Bayesian Optimization Method for Automated Machine Learning Model Selection.
Weipeng ZhouGang LuoPublished in: Poly/DMAH@VLDB (2020)
Keyphrases
- model selection
- sensitivity analysis
- optimization method
- machine learning
- bayesian learning
- covariate shift
- statistical inference
- marginal likelihood
- optimization algorithm
- cross validation
- bayesian model selection
- optimization methods
- hyperparameters
- bayesian methods
- parameter estimation
- genetic algorithm
- statistical learning
- managerial insights
- differential evolution
- bayesian approaches
- evolutionary algorithm
- simulated annealing
- posterior distribution
- markov chain monte carlo
- gaussian process
- nelder mead simplex
- feature selection
- optimization procedure
- variational inequalities
- sample size
- metaheuristic
- selection criterion
- unsupervised learning
- model selection criteria
- mixture model
- support vector machine
- bayesian information criterion
- maximum likelihood
- em algorithm
- optimal solution
- objective function
- bayesian networks