Hyperparameters and tuning strategies for random forest.
Philipp ProbstMarvin N. WrightAnne-Laure BoulesteixPublished in: WIREs Data Mining Knowl. Discov. (2019)
Keyphrases
- random forest
- hyperparameters
- model selection
- decision trees
- cross validation
- bayesian inference
- closed form
- support vector
- bayesian framework
- parameter settings
- random sampling
- feature set
- maximum likelihood
- prior information
- sample size
- em algorithm
- noise level
- incremental learning
- maximum a posteriori
- ensemble methods
- incomplete data
- feature selection
- parameter space
- genetic algorithm
- missing values
- error rate
- markov random field
- reinforcement learning
- image processing
- learning algorithm