Ensemble of Heterogeneous Classifiers for Improving Automated Tweet Classification.
Renhao CuiGagan AgrawalRajiv RamnathVinh Ngoc KhucPublished in: ICDM Workshops (2016)
Keyphrases
- multiple classifiers
- final classification
- ensemble classifier
- training set
- classifier ensemble
- classification algorithm
- classification systems
- support vector
- feature selection
- classification models
- multiple classifier systems
- majority voting
- decision trees
- individual classifiers
- classification method
- combining classifiers
- decision tree classifiers
- classifier combination
- accurate classifiers
- ensemble learning
- class labels
- supervised classification
- automated classification
- multi category
- concept drifting data streams
- training data
- generalization ability
- feature set
- optimum path forest
- classification process
- k nearest neighbour
- classification rate
- machine learning algorithms
- svm classifier
- machine learning methods
- classifier fusion
- text classification
- support vector machine svm
- imbalanced data
- multiclass classification
- probabilistic classifiers
- feature ranking
- ensemble methods
- binary classifiers
- decision boundary
- multi class
- benchmark datasets
- randomized trees
- support vector machine
- classification accuracy
- social media
- supervised learning
- trained classifiers
- weak learners
- training samples
- binary classification problems
- base classifiers
- rule based classifier
- roc curve
- learning algorithm
- weighted voting
- image classification
- cost sensitive
- random forest
- random forests
- machine learning