Linked Life Data

14751999

Source:http://linkedlifedata.com/resource/pubmed/id/14751999

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2004-3-22
pubmed:abstractText
We present a general purpose implementation of variable length Markov models. Contrary to fixed order Markov models, these models are not restricted to a predefined uniform depth. Rather, by examining the training data, a model is constructed that fits higher order Markov dependencies where such contexts exist, while using lower order Markov dependencies elsewhere. As both theoretical and experimental results show, these models are capable of capturing rich signals from a modest amount of training data, without the use of hidden states. AVAILABILITY: The source code is freely available at http://www.soe.ucsc.edu/~jill/src/
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
1367-4803
pubmed:author
pubmed:issnType
Print
pubmed:day
22
pubmed:volume
20
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
788-9
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Algorithms for variable length Markov chain modeling.
pubmed:affiliation
Center for Biomolecular Science and Engineering, School of Engineering, University of California, Santa Cruz, CA 95064, USA. jill@soe.ucsc.edu
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't