Classification Spam Email with Elimination of Unsuitable Features with Hybrid of GA-Naive Bayes.
O. M. E. EbadatiF. AhmadzadehPublished in: J. Inf. Knowl. Manag. (2019)
Keyphrases
- naive bayes
- classification accuracy
- naive bayes classifier
- decision trees
- naive bayesian classifier
- text classification
- spam filtering
- bayesian classifier
- classification algorithm
- averaged one dependence estimators
- spam detection
- anti spam
- logistic regression
- uci datasets
- feature space
- probabilistic classifiers
- feature selection
- cost sensitive
- email spam
- training data
- feature set
- uci data sets
- feature vectors
- training set
- genetic algorithm
- classification models
- augmented naive bayes
- feature subset
- combining classifiers
- genetic algorithm ga
- support vector
- text classifiers
- text categorization
- support vector machine
- naive bayes models
- bayesian network classifiers
- spam filters
- feature extraction
- class labels
- svm classifier
- text mining
- spam emails
- machine learning
- tree augmented naive bayes
- conditional independence assumption
- attribute dependencies
- bayesian classifiers
- base classifiers
- evolutionary algorithm
- model selection
- multiple classifiers
- unlabeled data
- phishing emails
- independence assumption
- training examples
- bayesian networks
- benchmark datasets
- supervised classification