Research Article
Feature Extraction with Ordered Mean Values for Content Based Image Classification
Table 18
Confusion matrix for Caltech dataset for feature extraction with DST (KNN classifier).
| a | b | c | d | e | f | g | h | i | j | k | l | m | n | o | p | q | r | s | t | ← classified as |
| 8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 81 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ∣ a = Airplane | 0 | 97 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | ∣ b = Bonsai | 0 | 0 | 47 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ∣ c = Panther | 0 | 0 | 0 | 60 | 0 | 2 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | ∣ d = Dalmatian | 0 | 0 | 0 | 0 | 61 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ∣ e = Dolphin | 0 | 0 | 0 | 0 | 0 | 433 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | ∣ f = Faces | 0 | 0 | 0 | 0 | 0 | 3 | 63 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ∣ g = Flamingo | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 31 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | ∣ h = Deer | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 88 | 0 | 0 | 0 | 10 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | ∣ i = Piano | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 26 | 0 | 0 | 2 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | ∣ j = Skates | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 29 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ∣ k = Metronome | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 39 | 0 | 0 | 0 | 0 | 0 | 0 | 34 | 0 | ∣ l = Minar | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 791 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ∣ m = Motorbike | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 31 | 0 | 0 | 0 | 0 | 0 | 0 | ∣ n = Panda | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 52 | 1 | 0 | 0 | 0 | 0 | ∣ o = Football | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 0 | 0 | 55 | 0 | 0 | 0 | 0 | ∣ p = Stopsign | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 80 | 0 | 0 | 0 | ∣ q = Sunflower | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 61 | 0 | 0 | ∣ r = Tree | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 36 | 0 | 0 | 0 | 0 | 0 | 0 | 34 | 0 | ∣ s = Tomb | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 8 | 0 | 0 | 1 | 0 | 0 | 0 | 228 | ∣ t = Watches |
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