A comparison of random forest variable selection methods for classification prediction modeling.
Jaime Lynn SpeiserMichael E. MillerJanet ToozeEdward H. IpPublished in: Expert Syst. Appl. (2019)
Keyphrases
- random forest
- variable selection
- cross validation
- machine learning methods
- preprocessing
- decision trees
- decision tree learning algorithms
- benchmark datasets
- model selection
- feature set
- machine learning
- ensemble classifier
- bayesian networks
- classification models
- feature ranking
- neural network
- random forests
- ensemble methods
- input variables
- genetic algorithm
- multi class
- data analysis
- training set
- feature vectors
- support vector machine svm
- image classification
- classification accuracy
- dimensionality reduction