Title :
Data Mining Algorithmic Research and Application Based on Information Entropy
Author :
Wan, Dingshwng ; Ren, Xiang ; Hu, Yuting
Author_Institution :
Coll. of Comput. & Inf. Eng., HoHai Univ., Nanjing
Abstract :
Traditional data mining predictive algorithm dealt little with original data set and did not make full use of the relationship of the data, as a result, numerous mathematical operation resources was wasted and also the accuracy of the predicted result was not very high. Against with this problem, correlation coefficient and information entropy were introduced, a data mining algorithmic based on information entropy was put forward, and an incremental predictive algorithm had been realized, too. Because the algorithm makes full use of the data setspsila interior relationship, it makes the forecasted results more accurate, and achieves a satisfied result.
Keywords :
data mining; entropy; data mining algorithmic research; incremental predictive algorithm; information entropy; interior relationship; Application software; Computer science; Data engineering; Data mining; Educational institutions; Information entropy; Lakes; Prediction algorithms; Software algorithms; Software engineering; Data correlation.; Data mining; Information entropy; Predictive algorithm;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.551