Research Article
Adaptive Online Sequential ELM for Concept Drift Tackling
Table 1
Concept drift scenarios, compared methods, and sequential patterns.
(a) The experiment design scenarios |
| Data set | Virtual drift | Real drift | Hybrid drift | Compared methods |
| SEA | — | ✓ | — | OS-ELM, CEOS-ELM, Kolter [20] | STAGGER | — | ✓ | — | OS-ELM, CEOS-ELM, Kolter [20] | MNIST | ✓ | ✓ | ✓ | OS-ELM, Offline ELM, ELM ensemble | MNIST + USPS | — | ✓ | ✓ | OS-ELM, offline ELM, ELM ensemble |
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(b) Concept drift sequential patterns |
| Data set | Sequential patterns scenarios | Cause of shift |
| SEA | Sudden change | Linear discriminant function | STAGGER | Sudden change | Logical discriminant rule | MNIST | Sudden change and recurring context | Additional attributes or classes | USPS | Recurring context | Additional attributes or classes |
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