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courses:rg:2013:hmm-perc-experiments [2013/03/13 01:47] ufal vytvořeno |
courses:rg:2013:hmm-perc-experiments [2013/04/01 12:33] (current) cechj5cm |
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N N X N X | N N X N X | ||
How would this result alter values of alfa_X,X,X, alfa_N, | How would this result alter values of alfa_X,X,X, alfa_N, | ||
- | Supposing that the best tag sequence | + | Supposing that the best tag sequence |
2. Suppose this tagged sentence as the only entry in your training data: | 2. Suppose this tagged sentence as the only entry in your training data: | ||
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(You might compare this problem to similar one in paper presented on RG in winter - http:// | (You might compare this problem to similar one in paper presented on RG in winter - http:// | ||
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+ | ===SHORT REPORT=== | ||
+ | Intro | ||
+ | Autors said that training perceptron is quicker and easier solution. | ||
+ | Definition | ||
+ | We defined structured perceptron and parametres for special case of structured perceptron. | ||
+ | Parameters are log of conditional probability for trigram words and conditional probability for word and tag. | ||
+ | αx,y,z = log P(z | x,y) | ||
+ | αt,w = log P(w| t) | ||
+ | Logs are used for precision | ||
+ | Then speaker show how work process of learning. | ||
+ | Autors then deal with separable and inseparable data. | ||
+ | They defined condition for inseparable data. | ||
+ | |||
+ | We spend rest of time solution of questions. During that solution were shown others fetatures of this percepton training. |