75 search results - page 1 / 15 » Building Text Classifiers Using Positive and Unlabeled Examp... |
ICDM
2003
IEEE
13 years 9 months ago
2003
IEEE
IJCAI
2003
13 years 5 months ago
2003
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 ...
AMT
2006
Springer
13 years 8 months ago
2006
Springer
Text classification using positive and unlabeled data refers to the problem of building text classifier using positive documents (P) of one class and unlabeled documents (U) of man...
KDD
2008
ACM
14 years 4 months ago
2008
ACM
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
ICML
2003
IEEE
14 years 5 months ago
2003
IEEE
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...