JOURNAL ARTICLE

Improvement and Application of Decision Tree C4.5 Algorithm

Jie YeLi-duo HOU

Year: 2018 Journal:   DEStech Transactions on Computer Science and Engineering   Publisher: Destech Publications

Abstract

The C4.5 algorithm as the most popular decision tree algorithm, there are still some deficiencies, C4.5 algorithm uses post-pruning to solve the over-fitting problem, but increase the modeling overhead, in response to this problem the idea of combining over-fitting branches ahead of time in the process of creating a decision tree is proposed and improved on the original C4.5 algorithm, which solves the problem of long decision-making time and large models of the decision tree. Experimental verification shows that the improved algorithm has a significant improvement in model simplification and model accuracy. The improved algorithm is applied to the "Engineering Quality Decision Support System" to provide supervision and decision-making support for the supervisory department.

Keywords:
Computer science Decision tree Pruning Incremental decision tree Decision tree model Algorithm ID3 algorithm Decision tree learning Overhead (engineering) Decision support system Process (computing) Data mining Machine learning Artificial intelligence

Metrics

7
Cited By
2.23
FWCI (Field Weighted Citation Impact)
0
Refs
0.90
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Decision-Making Techniques
Physical Sciences →  Computer Science →  Information Systems
Rough Sets and Fuzzy Logic
Physical Sciences →  Computer Science →  Computational Theory and Mathematics
Advanced Computational Techniques and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence

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