An empirical study on hyperparameter tuning of decision trees.
Rafael Gomes MantovaniTomás HorváthRicardo CerriSylvio Barbon JuniorJoaquin VanschorenAndré Carlos Ponce de Leon Ferreira de CarvalhoPublished in: CoRR (2018)
Keyphrases
- decision trees
- naive bayes
- hyperparameters
- logistic regression
- machine learning
- decision tree induction
- decision rules
- rule selection
- gaussian processes
- data mining methods
- machine learning algorithms
- predictive accuracy
- training set
- cross validation
- random forest
- model selection
- fine tuning
- maximum likelihood
- gaussian process
- rule induction
- multivariate decision trees
- decision tree learning
- decision tree algorithm
- meta learning
- parameter tuning
- incomplete data
- bayesian inference
- parameter settings
- incremental learning
- rule sets
- bayesian networks