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» Learning classifiers from only positive and unlabeled data
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WWW
2007
ACM
14 years 9 months ago
Combining classifiers to identify online databases
We address the problem of identifying the domain of online databases. More precisely, given a set F of Web forms automatically gathered by a focused crawler and an online database...
Luciano Barbosa, Juliana Freire
BMCBI
2007
91views more  BMCBI 2007»
13 years 8 months ago
A machine learning approach for the identification of odorant binding proteins from sequence-derived properties
Background: Odorant binding proteins (OBPs) are believed to shuttle odorants from the environment to the underlying odorant receptors, for which they could potentially serve as od...
Ganesan Pugalenthi, E. Ke Tang, Ponnuthurai N. Sug...
MM
2005
ACM
172views Multimedia» more  MM 2005»
14 years 2 months ago
Learning the semantics of multimedia queries and concepts from a small number of examples
In this paper we unify two supposedly distinct tasks in multimedia retrieval. One task involves answering queries with a few examples. The other involves learning models for seman...
Apostol Natsev, Milind R. Naphade, Jelena Tesic
AIME
1997
Springer
14 years 27 days ago
Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods
We used Machine Learning (ML) methods to learn the best decision rules to distinguish normal brain aging from the earliest stages of dementia using subsamples of 198 normal and 244...
William Rodman Shankle, Subramani Mani, Michael J....
KDD
2004
ACM
196views Data Mining» more  KDD 2004»
14 years 9 months ago
Adversarial classification
Essentially all data mining algorithms assume that the datagenerating process is independent of the data miner's activities. However, in many domains, including spam detectio...
Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. ...