Research Article
Recognition of Mixture Control Chart Pattern Using Multiclass Support Vector Machine and Genetic Algorithm Based on Statistical and Shape Features
Table 7
Recognition accuracies with the BP model.
| True pattern | Identified pattern (%) | NOR | CYC | IT | DT | US | DS | CT | CS | TS | CTS |
| NOR | 90 | 8 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | CYC | 4 | 88 | 4 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | IT | 0 | 0 | 56 | 32 | 10 | 2 | 0 | 0 | 0 | 0 | DT | 0 | 6 | 24 | 32 | 12 | 26 | 0 | 0 | 0 | 0 | US | 0 | 0 | 8 | 28 | 34 | 30 | 0 | 0 | 0 | 0 | DS | 0 | 0 | 0 | 2 | 10 | 74 | 10 | 2 | 2 | 0 | CT | 0 | 0 | 0 | 0 | 8 | 24 | 66 | 0 | 0 | 2 | CS | 0 | 0 | 0 | 0 | 0 | 0 | 22 | 78 | 0 | 0 | TS | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 10 | 84 | 4 | CTS | 0 | 2 | 0 | 2 | 6 | 2 | 0 | 14 | 16 | 58 |
| Average | 65.2 | | | | | | | | | |
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