Comparative Study of Principal Component Analysis (PCA) based On Decision Tree Algorithms

Authors

  • Aung Nway Oo

DOI:

https://doi.org/10.31695/IJASRE.2018.32767

Keywords:

Data mining (DM), Classification, Decision Tree (DT), Principal component analysis (PCA).

Abstract

Data mining (DM) can be viewed as a result of the natural evolution of information technology. The role of data mining approach is very important in computer science and knowledge engineering. A number of data mining approaches are used for classification. Classification is the process of finding a model that describes and distinguishes data classes or concepts. The decision tree (DT) approach is most useful in the classification problem. The research work analyses the efficiency of the Principal Component Analysis (PCA) based decision tree algorithms, namely J48, Classification and Regression Tree (CART) and Random Forest.

Downloads

Published

2018-06-05

How to Cite

Aung Nway Oo. (2018). Comparative Study of Principal Component Analysis (PCA) based On Decision Tree Algorithms. International Journal of Advances in Scientific Research and Engineering (IJASRE), ISSN:2454-8006, DOI: 10.31695/IJASRE, 4(6`), 122–126. https://doi.org/10.31695/IJASRE.2018.32767