PT Journal
AU Subbotin, S
   Oliinyk, A
   Levashenko, V
   Zaitseva, E
TI Diagnostic Rule Mining Based on Artificial Immune System for a Case of Uneven Distribution of Classes in Sample
SO Communications - Scientific Letters of the University of Zilina
PY 2016
BP 3
EP 11
VL 18
IS 3
DI 10.26552/com.C.2016.3.3-11
WP https://komunikacie.uniza.sk/artkey/csl-201603-0001.php
DE artificial immune system; instance; negative selection; classification; recognition error; sample
SN 13354205
AB The problem of development automation of classification rules synthesis on the basis of negative selection in the case of uneven distribution of classes in the sample is solved. The method for the synthesis of classification rules on the basis of negative selection in the case of uneven distribution of class instances of sample is proposed. This method uses a priori information about instances of all classes of the sample. The software implementing the proposed method is developed. Some experiments on the solution of practical problem of gas turbine air-engine blade diagnosis are conducted.
ER