Information Technology Reference
In-Depth Information
a.
*.+.+.d8.d5.d0.NET.d6.d6.d2.d4.d0.d4.d5.d1
+.*.*.d6.d1.*.LOE.d5.d1.d8.d7.d2.d4.d8.d1
*.d1.d3.d0.GT./.*.d3.d3.d8.d4.d7.d4.d8.d6
b.
Sub-ET 1
d 8
d 5
d 0
NET
d 6
d 6
Sub-ET 2
Sub-ET 3
d 5
d 1
d 6
d 1
LOE
d 5
d 1
d 8
d 7
Figure 4.8. Model evolved by GEP to diagnose breast cancer. a) The three-genic
chromosome encoding sub-ETs linked by addition. b) The sub-ETs codified by
each gene. Note that the expression of this chromosome is only complete after
linking with addition and applying the rounding threshold, which in this case is
equal to 0.5 (see model 4.9b).
4.2.2 Credit Screening
In credit screening the goal is to determine whether to approve or not a cus-
tomer's request for a credit card. Each sample in the dataset represents a real
credit card application and the output describes whether the bank granted the
credit card or not. This problem has 51 input attributes, all of them unex-
plained in the original dataset for confidentiality reasons.
The model presented here was obtained using the card1 dataset of
PROBEN1 where the binary 1-of- m encoding was again replaced by a 1-bit
encoding (“1” for approval and “0” for non-approval). The first 345 examples
were used for training and the last 172 were used for testing.
Search WWH ::




Custom Search