Linked Life Data

12767148

Source:http://linkedlifedata.com/resource/pubmed/id/12767148

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2003-5-27
pubmed:abstractText
The Support Vector Machine (SVM) classification algorithm, recently developed from the machine learning community, was used to diagnose breast cancer. At the same time, the SVM was compared to several machine learning techniques currently used in this field. The classification task involves predicting the state of diseases, using data obtained from the UCI machine learning repository. SVM outperformed k-means cluster and two artificial neural networks on the whole. It can be concluded that nine samples could be mislabeled from the comparison of several machine learning techniques.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0095-2338
pubmed:author
pubmed:issnType
Print
pubmed:volume
43
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
900-7
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:articleTitle
Diagnosing breast cancer based on support vector machines.
pubmed:affiliation
Department of Chemistry, Lanzhou University, Lanzhou 730000, China.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't