| |
k-NN
|
DT
|
SVM
|
|---|
| |
cv
|
test
|
cv
|
test
|
cv
|
test
|
|
S
O
|
0.814
|
0.778
|
0.752
|
0.703
|
0.838
|
0.904
|
|
S
O
*
|
0.812
|
0.781
|
0.766
|
0.702
|
0.839
|
0.904
|
|
T
O
|
0.812
|
0.819
|
0.770
|
0.739
|
0.822
|
0.905
|
|
T
O
*
|
0.817
|
0.844
|
0.788
|
0.756
|
0.825
|
0.909
|
|
S
T
|
0.814
|
0.777
|
0.771
|
0.734
|
0.838
|
0.904
|
|
S
T
*
|
0.817
|
0.775
|
0.800
|
0.729
|
0.842
|
0.904
|
- The accuracy of each base-learner trained with original data and with extra features added in SO/SO*, TO/TO* or ST/ST*. The values reported for each classifier are respectively the validation and test accuracies of the original representation and the new representation.
