Advances in Artificial Intelligence / 2014 / Article / Tab 8

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).

YearAlgorithm IDRule

199010MS = 0.97 * GS3 − 0.02

199110MS = 0.99 * GS3 − 0.02

199211MS = −0.0292 * (normalized) L2
   + 0.3947 * (normalized) GS2
   + 0.5996 * (normalized) GS3
   + 0.0068

199311MS = −0.1056 * (normalized) L2
   + 0.0094 * (normalized) P3
   + 0.0052 * (normalized) IE2
   + 0.4708 * (normalized) GS1
   + 0.523 * (normalized) GS3
   + 0.0044

199410MS = 1.04 * GS1 − 0.02

199510MS = 0.99 * GS1 − 0.02

199610MS = 1 * GS1 − 0.01

199710MS = 0.97 * GS3 + 0

199810MS = 1.06 * GS3 + 0.01

199911MS = −0.0237 * (normalized) L1
    − 0.0225 * (normalized) IE2
   + 0.296 * (normalized) GS1
   + 0.3055 * (normalized) GS2
   + 0.3722 * (normalized) GS3
   + 0.0272

20008MS = −0.1229 * L1 + 0.9571 * GS3 + 0.0769

20013If GS1 in (−inf–0.1] then MS = 0.03137
If GS1 in (0.3–0.4] then MS = 0.59189
If GS1 in (0.4–0.5] then MS = 0.041797
If GS1 in (0.5–0.6] then MS = 0.441048
If GS1 in (0.8–0.9] then MS = 0.093575
If GS1 in (0.9–inf) then MS = 1.0

200215, 11The 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

200311MS = −0.0024 * (normalized) L1
   + 0.0009 * (normalized) P2
   + 0.3401 * (normalized) GS1
   + 0.2689 * (normalized) GS2
   + 0.4899 * (normalized) GS3
   − 0.0007

200411MS = −0.0015 * (normalized) P2
   + 0.342 * (normalized) GS1
   + 0.2547 * (normalized) GS2
   + 0.4802 * (normalized) GS3
   − 0.0001

200511MS = −0.0028 * (normalized) IE3
   + 0.3304 * (normalized) GS1
   + 0.3268 * (normalized) GS2
   + 0.4712 * (normalized) GS3
   + 0.0002

20068MS = 0.1241 * GS1 + 0.3862 * GS2 + 0.6142 * GS3 + −0.0026

200711MS = 0.0049 * (normalized) CA3
   + 0.0012 * (normalized) P2
   + 0.3388 * (normalized) GS1
   + 0.3281 * (normalized) GS2
   + 0.471 * (normalized) GS3
   − 0.0056

20083If L3 in (−inf–0.1] then MS = 0.1942307
If L3 in (0.1–0.2] then MS = 0.479808
If L3 in (0.2–0.3] then MS = 0.073077
If L3 in (0.3–0.4] then MS = 0.019231
If L3 in (0.4–0.5] then MS = 0.980769
If L3 in (0.5–0.6] then MS = 0.2230765
If L3 in (0.6–0.7] then MS = 0.0826925
If L3 in (0.7–0.8] then MS = 0.042308
If L3 in (0.9–inf) then MS = 0.242308

20091MS = 0.403535