An Experimental Study of Diversity of Diabetes Disease Features by Bagging and Boosting Ensemble Method with Rule Based Machine Learning Classifier Algorithms.
Dhyan Chandra YadavSaurabh PalPublished in: SN Comput. Sci. (2021)
Keyphrases
- ensemble methods
- ensemble classifier
- benchmark datasets
- machine learning methods
- ensemble learning
- classifier ensemble
- machine learning
- decision trees
- base classifiers
- bootstrap sampling
- feature subset
- learning algorithm
- decision tree ensembles
- ensemble members
- random forests
- majority voting
- rotation forest
- base learners
- ensemble classification
- machine learning algorithms
- individual classifiers
- prediction accuracy
- feature selection
- random forest
- weak classifiers
- decision tree learning
- boosting algorithms
- feature set
- support vector machine
- weak learners
- feature space
- generalization ability
- classification algorithm
- multilabel classification
- meta learning
- classification models
- svm classifier
- subspace methods
- fusion method
- support vector
- training set
- multi class
- bias variance analysis
- randomized trees
- text classification
- data mining
- face recognition
- training data
- concept drift
- feature vectors
- genetic algorithm ga
- training examples
- model selection