Title :
Efficient splitting rules based on the probabilities of pre-assigned intervals
Author :
Cho, June-Suh ; Adam, Nabil R.
Author_Institution :
IBM T.J. Watson Res. Center, Hawthorne, NY, USA
Abstract :
The paper describes novel methods for classification in order to find an optimal tree. Unlike the current splitting rules that are provided by searching all threshold values, the paper proposes splitting rules that are based on the probabilities of pre-assigned intervals. In experiments, we demonstrate that our methods properly classify image objects based on new split rules
Keywords :
image classification; knowledge based systems; optimisation; probability; tree searching; classification methods; computational complexity; image object classification; optimal cutoff point; optimal tree; pre-assigned interval probabilities; split rules; splitting rules; threshold values; Error analysis; Milling machines; Radio access networks; Rivers; Search methods;
Conference_Titel :
Data Mining, 2001. ICDM 2001, Proceedings IEEE International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
0-7695-1119-8
DOI :
10.1109/ICDM.2001.989570
