International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
Improved training via incremental learning
Proceedings of the sixth international workshop on Machine learning
Decision Tree Induction Based on Efficient Tree Restructuring
Machine Learning
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Incremental Induction of Decision Trees
Machine Learning
Machine Learning
Option Decision Trees with Majority Votes
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Snitch: interactive decision trees for troubleshooting misconfigurations
SYSML'07 Proceedings of the 2nd USENIX workshop on Tackling computer systems problems with machine learning techniques
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Application of information theory to the construction of efficient decision trees
IEEE Transactions on Information Theory
Hybrid decision tree and naïve Bayes classifiers for multi-class classification tasks
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
This paper deals with some improvements to rule induction algorithms in order to resolve the tie that appear in special cases during the rule generation procedure for specific training data sets. These improvements are demonstrated by experimental results on various data sets. The tie occurs in decision tree induction algorithm when the class prediction at a leaf node cannot be determined by majority voting. When there is a conflict in the leaf node, we need to find the source and the solution to the problem. In this paper, we propose to calculate the Influence factor for each attribute and an update procedure to the decision tree has been suggested to deal with the problem and provide subsequent rectification steps.