feat: add topic 117 — stream-based & adaptive learning algorithms - #54
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ranjiGT
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Apr 27, 2026
ranjiGT
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- Gama's adaptive learning definition (Increment/Decrement operators)
- Sufficient statistics on streams: count, sum, sum-of-squares
- Recursive mean formula and Welford online std dev (verified on n=60 dataset)
- SimpleADWIN drift detector (Hoeffding-bound windowed)
- Online learning with SGDClassifier.partial_fit (batch vs adaptive comparison)
- Hoeffding Tree (VFDT) split criterion visualization
- Prequential (fading-window test-then-train) evaluation
- README: badge 116→117, project structure, Binder badge
- CHANGELOG: v1.4.0 entry
- Gama's adaptive learning definition (Increment/Decrement operators) - Sufficient statistics on streams: count, sum, sum-of-squares - Recursive mean formula and Welford online std dev (verified on n=60 dataset) - SimpleADWIN drift detector (Hoeffding-bound windowed) - Online learning with SGDClassifier.partial_fit (batch vs adaptive comparison) - Hoeffding Tree (VFDT) split criterion visualization - Prequential (fading-window test-then-train) evaluation - README: badge 116→117, project structure, Binder badge - CHANGELOG: v1.4.0 entry Co-authored-by: yatchmaster <yatchmaster@users.noreply.github.com>
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