Semi-supervised learning using frequent itemset and ensemble learning for SMS classification.
Ishtiaq AhmedRahman AliDonghai GuanYoung-Koo LeeSungyoung LeeTaeChoong ChungPublished in: Expert Syst. Appl. (2015)
Keyphrases
- semi supervised learning
- ensemble learning
- unlabeled data
- supervised learning
- generalization ability
- labeled and unlabeled data
- labeled data
- semi supervised
- co training
- class labels
- frequent itemsets
- machine learning
- text classification
- unsupervised learning
- ensemble classifier
- active learning
- training data
- ensemble methods
- classification accuracy
- training set
- support vector machine
- base classifiers
- pattern recognition
- support vector
- support vector machine svm
- machine learning methods
- classification algorithm
- concept drift
- learning algorithm
- itemsets
- feature extraction
- data points
- feature vectors
- text categorization
- training samples
- model selection
- test data
- decision trees
- association rules
- pairwise
- high dimensional
- multi class
- nearest neighbor
- k nearest neighbor
- machine learning algorithms
- training examples