Naive Bayes with Correlation Factor for Text Classification Problem
This is an incremental improvement for text classification tasks, particularly when dealing with limited training data.
The paper tackled the problem of Naive Bayes performing poorly with small training datasets in text classification by introducing a correlation factor to incorporate class correlations, resulting in better accuracy compared to traditional Naive Bayes on real-world data.
Naive Bayes estimator is widely used in text classification problems. However, it doesn't perform well with small-size training dataset. We propose a new method based on Naive Bayes estimator to solve this problem. A correlation factor is introduced to incorporate the correlation among different classes. Experimental results show that our estimator achieves a better accuracy compared with traditional Naive Bayes in real world data.