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 = 0.03137 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 
 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 = 0.1942307 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 
 2009  1  MS = 0.403535 

