Title :
The data mining method based on second learning
Author :
Li, Yan ; Li, Guo-gang ; Li, Fa-chao ; Jin, Chen-xia
Author_Institution :
Sch. of Sci., Hebei Univ. of Sci. & Technol., Shijiazhuang
Abstract :
Decision tree algorithm is not only the important part of machine learning, but also the most widely used data mining tool. At present, there are many algorithms of generating decision tree, but when the database which we rely on exists noise, high quality knowledge is hard to obtain by ID3 algorithm. In this paper, we propose the data mining method based on second learning in case of ID3 algorithm, and analyze the performance of our method by a concrete database. Theory analysis and simulation indicate that this method posses the feature of strong operability, and it can improve the reliability of obtained knowledge.
Keywords :
data mining; decision trees; learning (artificial intelligence); data mining method; decision tree algorithm; machine learning; second learning; Algorithm design and analysis; Concrete; Data analysis; Data mining; Decision trees; Machine learning; Machine learning algorithms; Noise generators; Performance analysis; Spatial databases; Accuracy rate; Decision tree; ID3 algorithm; Noise; Second learning;
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
DOI :
10.1109/ICMLC.2008.4620428
