원문정보
보안공학연구지원센터(IJDTA)
International Journal of Database Theory and Application
Vol.9 No.5
2016.05
pp.1-8
피인용수 : 0건 (자료제공 : 네이버학술정보)
목차
Abstract
1. Introduction
2. Introduction of Decision Tree
3. Construction and Pruning of Decision Tree
3.1. Construction of Decision Tree
3.2 Pruning of Decision Tree
3.3 Two Basic Pruning Strategy
3.4 Principle of Tree Pruning Optimization
4. ID3 Algorithm
4.1 Information Theory and Entropy
4.2 Information Gain
4.3 Analysis of ID3 Algorithm
5. C4.5 Algorithm
5.1 Concept of Information Gain Ratio
5.2. Combined with Continuous Value Attributes
5.3. Production of Regular
6. Analysis for Decision Tree Classification Algorithm
7. Decision Tree Classification Algorithm
8. Conclusions
References
1. Introduction
2. Introduction of Decision Tree
3. Construction and Pruning of Decision Tree
3.1. Construction of Decision Tree
3.2 Pruning of Decision Tree
3.3 Two Basic Pruning Strategy
3.4 Principle of Tree Pruning Optimization
4. ID3 Algorithm
4.1 Information Theory and Entropy
4.2 Information Gain
4.3 Analysis of ID3 Algorithm
5. C4.5 Algorithm
5.1 Concept of Information Gain Ratio
5.2. Combined with Continuous Value Attributes
5.3. Production of Regular
6. Analysis for Decision Tree Classification Algorithm
7. Decision Tree Classification Algorithm
8. Conclusions
References
저자정보
참고문헌
자료제공 : 네이버학술정보