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ECML
2006
Springer
13 years 10 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
ICDM
2008
IEEE
147views Data Mining» more  ICDM 2008»
14 years 1 months ago
Clustering Documents with Active Learning Using Wikipedia
Wikipedia has been applied as a background knowledge base to various text mining problems, but very few attempts have been made to utilize it for document clustering. In this pape...
Anna Huang, David N. Milne, Eibe Frank, Ian H. Wit...
PR
2006
127views more  PR 2006»
13 years 7 months ago
Unsupervised possibilistic clustering
In fuzzy clustering, the fuzzy c-means (FCM) clustering algorithm is the best known and used method. Since the FCM memberships do not always explain the degrees of belonging for t...
Miin-Shen Yang, Kuo-Lung Wu
EUSFLAT
2003
145views Fuzzy Logic» more  EUSFLAT 2003»
13 years 8 months ago
Proximity fuzzy clustering for web context analysis
This study extends the web classification approach through a proximity-based fuzzy clustering sensible to the influence of the page. The proximity-based fuzzy clustering works in ...
Vincenzo Loia, Witold Pedrycz, Sabrina Senatore
NN
2006
Springer
153views Neural Networks» more  NN 2006»
13 years 7 months ago
An incremental network for on-line unsupervised classification and topology learning
This paper presents an on-line unsupervised learning mechanism for unlabeled data that are polluted by noise. Using a similarity thresholdbased and a local error-based insertion c...
Shen Furao, Osamu Hasegawa