Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
Recently, data mining techniques have been utilized in various fields in order to effectively classify and analyze the information desired by a large number of data. Decision trees and clustering are basic and widely used techniques. We will use decision trees and clustering to analyze colon cancer and predict effective treatment. So, we will analyze the decision tree and clustering in detail to predict effective treatment and then study better treatment. In order to use various algorithms such as J48 decision trees and to selectively use the optimal algorithm for a specific situation, the fitness of the algorithm for each situation. In this study, we evaluated the performance of the algorithm based on the results of 10 cross validation using decision trees and explained the treatment prediction of colon cancer based on the result of clustering. We analyzed the performance of the algorithm and the results of the experimental data.
How to cite this article:
Yong Gyu Jung and Min Soo Kang. Effective Prediction Model for Colorectal Cancer using Decision
Tree and Clustering.
DOI: https://doi.org/10.36478/jeasci.2018.903.909
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2018.903.909