Research Article

# Analysis of Changes in Market Shares of Commercial Banks Operating in Turkey Using Computational Intelligence Algorithms

## Table 8

The rules generated by the best algorithm for each year (dataset).
 Year Algorithm ID Rule 1990 10 MS = 0.97 * GS3 − 0.02 1991 10 MS = 0.99 * GS3 − 0.02 1992 11 MS = −0.0292 * (normalized) L2    + 0.3947 * (normalized) GS2    + 0.5996 * (normalized) GS3    + 0.0068 1993 11 MS = −0.1056 * (normalized) L2    + 0.0094 * (normalized) P3    + 0.0052 * (normalized) IE2    + 0.4708 * (normalized) GS1    + 0.523 * (normalized) GS3    + 0.0044 1994 10 MS = 1.04 * GS1 − 0.02 1995 10 MS = 0.99 * GS1 − 0.02 1996 10 MS = 1 * GS1 − 0.01 1997 10 MS = 0.97 * GS3 + 0 1998 10 MS = 1.06 * GS3 + 0.01 1999 11 MS = −0.0237 * (normalized) L1     − 0.0225 * (normalized) IE2    + 0.296 * (normalized) GS1    + 0.3055 * (normalized) GS2    + 0.3722 * (normalized) GS3    + 0.0272 2000 8 MS = −0.1229 * L1 + 0.9571 * GS3 + 0.0769 2001 3 If GS1 in (−inf–0.1] then MS = 0.03137If GS1 in (0.3–0.4] then MS = 0.59189If GS1 in (0.4–0.5] then MS = 0.041797If GS1 in (0.5–0.6] then MS = 0.441048If GS1 in (0.8–0.9] then MS = 0.093575If GS1 in (0.9–inf) then MS = 1.0 2002 15, 11 The best performed algorithm is bagging. But the rules generated by bagging are very long. Instead of giving these long rules, a rule generated by the second best algorithm (SMOreg) is given. MS = −0.2014 * (normalized) CA2    − 0.0089 * (normalized) L1    − 0.0859 * (normalized) IE2    + 0.7895 * (normalized) GS1    + 0.1961 2003 11 MS = −0.0024 * (normalized) L1    + 0.0009 * (normalized) P2    + 0.3401 * (normalized) GS1    + 0.2689 * (normalized) GS2    + 0.4899 * (normalized) GS3    − 0.0007 2004 11 MS = −0.0015 * (normalized) P2    + 0.342 * (normalized) GS1    + 0.2547 * (normalized) GS2    + 0.4802 * (normalized) GS3    − 0.0001 2005 11 MS = −0.0028 * (normalized) IE3    + 0.3304 * (normalized) GS1    + 0.3268 * (normalized) GS2    + 0.4712 * (normalized) GS3    + 0.0002 2006 8 MS = 0.1241 * GS1 + 0.3862 * GS2 + 0.6142 * GS3 + −0.0026 2007 11 MS = 0.0049 * (normalized) CA3    + 0.0012 * (normalized) P2    + 0.3388 * (normalized) GS1    + 0.3281 * (normalized) GS2    + 0.471 * (normalized) GS3    − 0.0056 2008 3 If L3 in (−inf–0.1] then MS = 0.1942307If L3 in (0.1–0.2] then MS = 0.479808If L3 in (0.2–0.3] then MS = 0.073077If L3 in (0.3–0.4] then MS = 0.019231If L3 in (0.4–0.5] then MS = 0.980769If L3 in (0.5–0.6] then MS = 0.2230765If L3 in (0.6–0.7] then MS = 0.0826925If L3 in (0.7–0.8] then MS = 0.042308If L3 in (0.9–inf) then MS = 0.242308 2009 1 MS = 0.403535