The comparison of Naive Bayesian and Decision Tree Based on Principal Component Analysis
Hongbo Shi · Computer Knowledge and Technology · 2010
Naive Bayes and decision tree classifications have been widely used due to their high performance and simplicity, and many scholars are studying how to process the data before classification in order to enhance the performance of their classification.This article first extracted feature data using principal component analysis, and then processed the data on the use of naive Bayes and decision tree classifications, and experimental results were analyzed and compared the impact of the principal component analysis on their classification performance.