A classifier of the Random Forest type based on GMDH, logistic transformation and positional voting.
Yaroslav HladkyiOleg RadchenkoVladimir PavlovOleksandr MatviichukOlena HorodetskaPublished in: CSIT (2023)
Keyphrases
- random forest
- feature set
- decision trees
- fold cross validation
- random forests
- ensemble learning
- ensemble classifier
- logistic regression
- majority voting
- ensemble methods
- training data
- classification accuracy
- training set
- feature importance
- group method of data handling
- training samples
- multi label
- feature selection
- individual classifiers
- decision tree learning algorithms
- classification models
- feature space
- base classifiers
- bayesian classifier
- naive bayes
- feature ranking
- artificial neural networks
- image processing
- machine learning
- neural network