QPC+NB on Sonar data
Sonar
1x10 CV
normalization
QPC parameters
lr = 0.1
optimization = gradient descent
| NaiveBayes | |
|---|---|
| acc. | std. |
| 70.64 | 13.80 |
| Dim. | QPC + NB | QPC2 + NB | ||
|---|---|---|---|---|
| acc. | std. | acc. | std. | |
| 1 | 74.02 | 14.25 | 73.02 | 10.55 |
| 2 | 74.52 | 13.29 | 74.97 | 10.29 |
| 3 | 76.02 | 13.93 | 76.95 | 12.21 |
| 4 | 77.90 | 12.51 | 78.85 | 10.32 |
| 5 | 77.42 | 12.65 | 79.83 | 10.18 |
| 6 | 76.47 | 12.72 | 77.90 | 11.68 |
| 7 | 76.95 | 12.79 | 77.45 | 11.81 |
| 8 | 76.95 | 11.77 | 78.88 | 10.75 |
| 9 | 78.38 | 11.91 | 78.40 | 11.21 |
| 10 | 79.33 | 12.30 | 78.90 | 11.40 |
Dim. - number of linear ptojections generated by QPC
QPC2 - fast QPC method based on subset of reference prototypes
NB - Naive Bayes with normal distribution assumption
