Design of experiments and response surface methodology to tune machine learning hyperparameters, with a random forest case-study.
Gustavo A. Lujan-MorenoPhillip R. HowardOmar RojasDouglas C. MontgomeryPublished in: Expert Syst. Appl. (2018)
Keyphrases
- random forest
- machine learning
- decision trees
- response surface methodology
- feature set
- hyperparameters
- pattern recognition
- prior information
- ensemble methods
- data analysis
- fold cross validation
- neural network
- high dimensional
- active learning
- model selection
- prediction model
- computer vision
- noise level
- support vector regression