# CRF Training Algorithm

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A CRF Training Algorithm is a graphical model training algorithm that accepts a CRF model family and can be applied by a CRF training system (to solve a CRF training task to produce a CRF structure).

## References

### 2016

• http://www.datasciencecentral.com/profiles/blogs/conditional-random-fields-crf-short-survey
• QUOTE: The time complexity of the training process is large enough: $\begin{equation*} O(mNTQ2nS), \end{equation*}$, where:
• m is the number of training iterations
• N is the number of training data sequences
• T is the average length of training sequences
• Q is the number of class labels
• n is the number of CRF features
• S is the searching time of the optimization algorithm (for example, L-BFGS algorithm, which is considered good for this).
• In practical implementation, the computational time is often larger due to many other operations like numerical scaling, smoothing etc.