The problem of object generalization with account for the necessity of processing the incomplete and inconsistent information stored in real databases is considered. It is suggested to use means of rough sets theory and decision trees to generalize the information stored in real databases. Noise models are presented, and a noise effect on the operation of generalization algorithms using the methods of building decision trees is developed. The algorithm for unknown values reconstruction in learning samples subjected to the noise effect based on the nearest neighbour method is proposed. The results of program modeling are brought out.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 email@example.com
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 firstname.lastname@example.org