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» Learning Functions from Imperfect Positive Data
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IJCAI
2003
13 years 8 months ago
Learning to Classify Texts Using Positive and Unlabeled Data
In traditional text classification, a classifier is built using labeled training documents of every class. This paper studies a different problem. Given a set P of documents of a ...
Xiaoli Li, Bing Liu
IJCNN
2000
IEEE
13 years 12 months ago
Extracting Distributed Representations of Concepts and Relations from Positive and Negative Propositions
Linear Relational Embedding (LRE) was introduced (Paccanaro and Hinton, 1999) as a means of extracting a distributed representation of concepts from relational data. The original ...
Alberto Paccanaro, Geoffrey E. Hinton
KDD
2005
ACM
161views Data Mining» more  KDD 2005»
14 years 8 months ago
Combining email models for false positive reduction
Machine learning and data mining can be effectively used to model, classify and discover interesting information for a wide variety of data including email. The Email Mining Toolk...
Shlomo Hershkop, Salvatore J. Stolfo
CSB
2004
IEEE
106views Bioinformatics» more  CSB 2004»
13 years 11 months ago
Positive Sample Only Learning (PSOL) for Predicting RNA Genes in E. coli
RNA genes lack most of the signals used for protein gene identification. A major shortcoming of previous discriminative methods to distinguish functional RNA (fRNA) genes from oth...
Richard F. Meraz, Xiaofeng He, Chris H. Q. Ding, S...
ICML
2003
IEEE
14 years 8 months ago
Learning with Positive and Unlabeled Examples Using Weighted Logistic Regression
The problem of learning with positive and unlabeled examples arises frequently in retrieval applications. We transform the problem into a problem of learning with noise by labelin...
Wee Sun Lee, Bing Liu