Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [conditional-random-field]

61 questions
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Intuitive difference between hidden Markov models and conditional random fields

I understand that HMMs (Hidden Markov Models) are generative models, and CRF are discriminative models. I also understand how CRFs (Conditional Random Fields) are designed and used. What I do not understand is how they are different from HMMs? I…
user1343318
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Implementation of CRF in python

Is there a popular implementation of Conditional Random Fields in Python? I can't seem to find any that is widely used and popular!
garak
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What's the difference between a Markov Random Field and a Conditional Random Field?

If I fix the values of the observed nodes of an MRF, does it become a CRF?
someone
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Deep Learning vs Structured Learning

I am interested in the differences between using large, deep learning networks vs Probabilistic graphical models (PGMs), like Random Field models, for structured learning (e.g. on images, or labels of arbitrary graphs on surfaces, etc...). For…
user3658307
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Python package that allows to train a CRF on two datasets

I am looking for a Python package that allows to train a conditional random field (CRF) on two datasets. For example: I have two datasets, dataset A and dataset B. I want to train a conditional random field on dataset A, then train the CRF on…
Franck Dernoncourt
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Sequence length when training a conditional random field (CRF)

I am training a conditional random field (CRF) to perform named entity recognition. I have 1000 documents, each containing from 100 to 500 sentences. During the training phase, is it better to train sentence per sentence, or document per document?…
Franck Dernoncourt
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Relation between Gaussian Processes and Gaussian Markov Random Fields

As a non expert in the field, I am relating Gaussian Processes (GP) and Gaussian Markov Random Fields (GMRF). I might just be confused by the fact that different resources use different formalism. Here I try to report the main definitions and my…
asdf
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HMM and CRF: the label bias problem and I-equivalence

I have a question about the label bias problem in HMM and CRF. I understand that HMM and MEMM suffer from the label bias problem, which is a preference for states with fewer transitions. The problem is due to the fact that in HMM and MEMM use local…
Mou
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How can I implement a CRF feature function?

It is said that a feature function can represent anything, the first or the last word of a sentence, a capital character and etc. But how exactly can I represent them in such a form: $F_j(x, y)$ or $\sum_i f_j(y_{i-1}, y_i, \bar x, i)$ as explained…
Lerner Zhang
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Is every Conditional Random Field simply a Markov Random Field with restricted structure?

If I have a graph $H$ with nodes $\mathbf{X} \cup \mathbf{Y}$, and a set of factors $\phi_1(D_1), \ldots, \phi_k(D_k)$, where for each $i$, $D_i \not\subset X$, then doesn't this define both a MRF and a CRF? If we wanted to view this as a Markov…
Fequish
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Can I simulate a random field with nested variogram by a summation of independently simulated random field for each componnet of the nested variogram?

I want to simulate a random field $Z(u)$ that has a nested variogram, say $\gamma(h)=\gamma_1(h) + \gamma_2(h) + \gamma_3(h)$, assuming the variogram is isotropic. Whether can I simuate independently three random fields: $Z_1(u)$ with correlation…
emberbillow
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Sequential Prediction: Data Modeling and Classical Algorithms

I have data that can be called demographic data. Raw data Person 0001 \begin{array}{|c|c|} \hline Feb\,1981- Apr\,85 & engaged\,\,in\,\,\underline{activity}\,\,\textit{A}\,\,of \,\,\underline{type}\,\,\textbf{square}\,\\ \hline Apr\,1985- July\,86 &…
stack not overflowing
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HMM ever better than CRF?

For classifying a sequence of instances, are there any specific circumstances that make Hidden Markov Models (HMMs) more accurate than Conditional Random Fields (CRFs)? I have seen several papers that show CRFs outperforming HMMs, but none showing…
Mzzzzzz
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What means random field in "Conditional Random Field"

I have studied about CRF but the popular papers and tutorials have not describe the philosophy of CRF. I see the terms "Field", "Random Field" and "Conditional" from terminological aspect. But the papers, blogs and forums did not define the…
mhbashari
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Sequence tagging with additional structure

I am looking for pointers (papers, algorithms etc) for learning models for sequence tagging but which allow for additional structure. Consider Part of Speech Tagging, I could train a CRF which would work fine, but suppose I want to impose an…
A.D
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