The process demonstrates the influence of the parameter
C on the average classification error rate of the
linear SVM in the case of the Heart Disease data
set. We consider linear SVMs with different
values, each of which is an integer power of 2:
C = 2^n, where
-13 <= n <= 6. The average
classification error rate from 10-fold cross-validation is determined
for each linear SVM.
Heart Disease [UCI MLR]
The data set was donated to the UCI Machine Learning Repository by R. Detrano [Detrano et al.].
Figure 8.12. The average classification error rate of the linear SVM obtained from
10-fold cross-validation against the value of the parameter
C, where the horizontal axis is scaled
The figure shows that the average classification error rate is minimal
when the value of the parameter
2^-8. Larger values of
result in a slightly worse average classification performance. However,
values closer to zero give worse result.
Thus, the performance of the linear SVM seems not to be sensitive to
the value of the parameter
C in this case.