PCA-NB Algorithm to Enhance the Predictive Accuracy

摘要

This paper mainly deals with feature extraction algorithm used to improve the predicted accuracy of the classification. This paper applies with Principal Component analysis as a feature evaluator and ranker for searching method. Naive Bayes algorithm is used as a classification algorithm. It analyzes the hepatitis patients from the UC Irvine machine learning repository. The results of the classification model are accuracy and time. Finally, it concludes that the proposed PCA-NB algorithm performance is better than other classification techniques for hepatitis patients.