The context tree weighting method (CTW) is a lossless compression and prediction algorithm by Willems, Shtarkov & Tjalkens 1995. The CTW algorithm is among the very few such algorithms that offer both theoretical guarantees and good practical performance (see, e.g. Begleiter, El-Yaniv & Yona 2004).
The CTW algorithm is an “ensemble method,” mixing the predictions of many underlying variable order Markov models, where each such model is constructed using zero-order conditional probability estimators.
References
- Willems; Shtarkov; Tjalkens (1995), "The Context-Tree Weighting Method: Basic Properties", IEEE Transactions on Information Theory (IEEE Transactions on Information Theory) 41 (3): 653–664, doi:10.1109/18.382012, https://ieeexplore.ieee.org/document/382012
- Willems; Shtarkov; Tjalkens (1997), Reflections on "The Context-Tree Weighting Method: Basic Properties", 47, IEEE Information Theory Society Newsletter, https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.109.1872&rep=rep1&type=pdf
- Begleiter; El-Yaniv; Yona (2004), On Prediction Using Variable Order Markov Models, 22, Journal of Artificial Intelligence Research: Journal of Artificial Intelligence Research, pp. 385–421, https://www.jair.org/index.php/jair/article/view/10394
External links
 | Original source: https://en.wikipedia.org/wiki/Context tree weighting. Read more |
