의사결정트리와 신경망을 결합한 모델 성능비교

• 영문명: Performance evaluation for Ensemble combined Decision Trees with neural network Classifiers
• 발행기관: 한국IT마케팅학회
• 저자명: 신우섭(Woo Seub Shin) 권영만(Young Man Kwon)
• 간행물 정보: 『한국IT마케팅학회 논문집』2015 IT마케팅학회 논문집 Vol.1 No.1, 121~123쪽, 전체 3쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2015.11.20

영문 초록

In this paper, we have developed a new algorithm that combined decision trees and neuron network as the main purpose of R program. Research background was initiated due to the low performance of the classification decision tree. Research goal is combine to decision trees and neural networks to performance for improved classification. Experimental method is to compare the decision tree and random forest for obesity data and iris data whether classfication performance. The experimental results is error rate that higher than the combined model, and combined model is classification performance can be seen that good.

목차

Abstract

I. 서론

II. 관련연구

III. 제안된 시스템과 실험 결과

IV. 결론

참고문헌

키워드

의사결정트리 신경망 의사결정트리와 신경망 결합모델