The SVM was tested upon three separate algorithms.
- Linear
- Polynomial
- RBF
- Sigmoid
Different SVM kernels for IRIS dataset - Source: scikit-learn docs
|
Precision |
Recall |
F1-Score |
Support |
0.0 |
1.0 |
1.0 |
1.0 |
12 |
1.0 |
1.0 |
1.0 |
1.0 |
11 |
2.0 |
1.0 |
1.0 |
1.0 |
18 |
Accuracy |
|
|
1.0 |
41 |
Macro Avg |
1.0 |
1.0 |
1.0 |
41 |
Weighted Avg |
1.0 |
1.0 |
1.0 |
41 |
|
Precision |
Recall |
F1-Score |
Support |
0.0 |
1.0 |
1.0 |
1.0 |
12 |
1.0 |
1.0 |
0.55 |
0.71 |
11 |
2.0 |
0.78 |
1.0 |
0.88 |
18 |
Accuracy |
|
|
0.88 |
41 |
Macro Avg |
0.93 |
0.85 |
0.86 |
41 |
Weighted Avg |
0.90 |
0.88 |
0.87 |
41 |
|
Precision |
Recall |
F1-Score |
Support |
0.0 |
1.0 |
1.0 |
1.0 |
12 |
1.0 |
1.0 |
1.0 |
1.0 |
11 |
2.0 |
1.0 |
1.0 |
1.0 |
18 |
Accuracy |
|
|
1.0 |
41 |
Macro Avg |
1.0 |
1.0 |
1.0 |
41 |
Weighted Avg |
1.0 |
1.0 |
1.0 |
41 |
|
Precision |
Recall |
F1-Score |
Support |
0.0 |
1.0 |
1.0 |
1.0 |
12 |
1.0 |
1.0 |
0.45 |
0.62 |
11 |
2.0 |
0.78 |
0.78 |
0.88 |
18 |
3.0 |
0.0 |
0.0 |
0.0 |
0 |
Accuracy |
|
|
0.76 |
41 |
Macro Avg |
0.75 |
0.56 |
0.62 |
41 |
Weighted Avg |
1.00 |
0.76 |
0.84 |
41 |