Computer Science
8 years ago

Boosting text classification accuracy with hybrid classifier approach revolutionizes accuracy rates

Knowledge-Based Systems
Chinese text classification by the Naïve Bayes Classifier and the associative classifier with multiple confidence threshold values
Shing-Hwa Lu, Ding-An Chiang, Huan‐Chao Keh, Huihua Huang

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Combining the Naïve Bayes Classifier and the associative classifier improves text classification accuracy. By using different confidence threshold values for class association rules, the classifiers complement each other's strengths. The approach optimizes classification results by selecting high-accuracy class association rules. Unclassified cases are then classified using the Naïve Bayes Classifier. Experimental results demonstrate that this combined approach yields better classification outcomes than using a single classifier.