Recommending Learning Algorithms and Their Associated Hyperparameters.
Michael R. SmithLogan MitchellChristophe G. Giraud-CarrierTony R. MartinezPublished in: CoRR (2014)
Keyphrases
- hyperparameters
- learning algorithm
- model selection
- cross validation
- bayesian inference
- random sampling
- closed form
- support vector
- bayesian framework
- active learning
- maximum likelihood
- em algorithm
- gaussian process
- prior information
- incremental learning
- maximum a posteriori
- noise level
- sample size
- machine learning algorithms
- incomplete data
- learning problems
- gaussian processes
- parameter space
- machine learning
- expectation maximization
- supervised learning
- learning tasks
- grid search
- computer vision
- marginal likelihood
- missing values
- parameter settings
- back propagation
- learning process
- training data
- missing data
- feature selection
- probabilistic model
- multiscale
- decision trees