Enhanced ensemble-based classifier with boosting for pattern recognition.
Eva VolnáMartin KotyrbaPublished in: Appl. Math. Comput. (2017)
Keyphrases
- pattern recognition
- ensemble learning
- weak learners
- multiple classifier systems
- weak classifiers
- ensemble classifier
- ensemble methods
- base classifiers
- multiple classifiers
- classifier ensemble
- ensemble classification
- base learners
- individual classifiers
- strong classifier
- feature selection
- combining classifiers
- classifier combination
- majority voting
- learning algorithm
- training data
- final classification
- decision stumps
- binary classification problems
- adaboost algorithm
- decision trees
- training set
- random forests
- accurate classifiers
- neural network
- multi class classification
- generalization ability
- machine learning
- feature set
- binary classifiers
- boosting algorithms
- improving classification accuracy
- randomized trees
- ensemble members
- decision tree classifiers
- concept drift
- computer vision
- image processing
- feature extraction
- multi class
- training samples
- class labels
- pattern recognition problems
- prediction accuracy
- weighted voting
- support vector machine
- random forest
- linear classifiers
- decision forest
- naive bayes
- face detector
- labeled data
- supervised learning
- svm classifier
- feature space
- classification models