C4.5 - Open Access .click

2007 International Conference on Machine Learning and Cybernetics, 2007
C4.5 is a well-known machine learning algorithm used extensively, however, its runtime performance is sacrificed for the consideration of the limited main memory at that time. We present a fast implementation of C4.5 algorithm, named FC4.5(Fast C4.5).
Ping He, Ling Chen, Xiao-Hua Xu
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Improved C4.5 Decision Tree

2010 International Conference on Internet Technology and Applications, 2010
Based on analysed the various decision tree algorithm,improve the c4.5 classification analysis technique,proposed based on the c4.5 classification analysis technique churn prediction--ICDT classification algorithm. Through case analysis and discussion,proof ICDT algorithm In the telecommunications customer Forecast.
Wenguang Jia, LiJing Huang
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NeC4.5: neural ensemble based C4.5

IEEE Transactions on Knowledge and Data Engineering, 2004
Decision tree is with good comprehensibility while neural network ensemble is with strong generalization ability. These merits are integrated into a novel decision tree algorithm NeC4.5. This algorithm trains a neural network ensemble at first. Then, the trained ensemble is employed to generate a new training set through replacing the desired class ...
null Zhi-Hua Zhou, null Yuan Jiang
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C4.5 decision forests

Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170), 2002
Much of previous attention on decision trees focuses on the splitting criteria and optimization of tree sizes. The dilemma between overfitting and achieving maximum accuracy is seldom resolved. We propose a method to construct a decision tree based classifier that maintains highest accuracy on training data and improves on generalization accuracy as it
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data mining
classification
naïve bayes

c4.5 algorithm
machine learning
qa75.5-76.95

electronic computers. computer science
naive bayes
decision tree