my question about iir

[shuyo]

As I can not lecture a general information on CRF here...

This implementation has 2 type of parameters, feature vectors and regularization (none/L1/L2 and the inverse of regularity).
The feature vectors are specified as list of function objects which return binary value(0 or 1), and consist on 2 type feature, f(y_{i-1}, y_i) and g(y_i, x_i) (see the below link)

http://www.slideshare.net/shuyo/crf-web/29 (Although it is written in Japanese, the graphical model is universal :D)

The 'main' method on crf.py is a sample code to use CRF class. I am happy you to read it.
Thanks.

[goog]

Hi! which formula does the gradient_likelihood() function apply, the expectation here I can't understand it . It seems unlike to the one in P30.(1) in your PPT. or If possible ,please write the gradient_likelihood() formulas to my mail. Thanks very much!!!