New Voting Schemas for Heterogeneous Ensemble of Classifiers in the Problem of Football Results Prediction.
Szymon GlowaniaJan KozakPrzemyslaw JuszczukPublished in: KES (2022)
Keyphrases
- majority voting
- ensemble classifier
- weighted voting
- ensemble learning
- ensemble methods
- prediction accuracy
- voting scheme
- classifier ensemble
- multiple classifiers
- ensemble classification
- training data
- ensemble pruning
- individual classifiers
- feature selection
- training set
- voting schemes
- combining classifiers
- multiple classifier systems
- decision trees
- decision tree classifiers
- majority vote
- fusion methods
- concept drift
- randomized trees
- final classification
- base classifiers
- random forest
- imbalanced data
- databases
- ensemble members
- voting method
- neural network
- support vector
- neural network ensemble
- knn
- accurate classifiers
- concept drifting data streams
- classifier combination
- combining multiple
- random forests
- generalization ability
- classification algorithm
- machine learning algorithms
- machine learning
- learning algorithm
- rule induction algorithm
- xml documents
- support vector machine
- feature set
- diversity measures
- naive bayes
- video data
- classification models
- linear classifiers
- weak classifiers
- feature ranking
- heterogeneous data sources