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Context tree weighting
CTW (англ. Context Tree Weighting — взвешивание контекстного дерева) — алгоритм предсказания и сжатия без потерь, созданный Willems, Shtarkov, and Tjalkens (1995), «» . CTW является одним из немногих алгоритмов, которые обеспечивают как хорошие теоретические показатели, так и хорошо показывают себя на практике (например, см., Begleiter, El-Yaniv, and Yona (2004), «» ). При оценке вероятности символа алгоритм CTW с определённым весом смешивает статистику предсказаний многих моделей Маркова разного порядка, каждая из которых создаётся на основе условных вероятностных оценок нулевого порядка.
External links
- Willems, Shtarkov, and Tjalkens (1995), «The Context-Tree Weighting Method: Basic Properties», vol. 41, IEEE Transactions on Information Theory
- Begleiter, El-Yaniv, and Yona (2004), «On Prediction Using Variable Order Markov Models», vol. 22, Journal of Artificial Intelligence Research: Journal of Artificial Intelligence Research, сс. 385–421, <http://www.jair.org/media/1491/live-1491-2335-jair.pdf>
- Публикации на тему CTW. Ссылки на исходные коды.
- Официальная страница CTW.
- Документы по CTW.
- Context Tree Switching (CTS) - вариант CTW.
Категория:
- Алгоритмы сжатия без потерь
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