1344 search results - page 7 / 269 » Learning Classifiers from Semantically Heterogeneous Data |
KDD
2008
ACM
14 years 7 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 ...
WILF
2005
Springer
14 years 28 days ago
2005
Springer
Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
WWW
2008
ACM
14 years 8 months ago
2008
ACM
This paper presents a general framework for building classifiers that deal with short and sparse text & Web segments by making the most of hidden topics discovered from larges...
CVPR
2004
IEEE
14 years 9 months ago
2004
IEEE
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
DMIN
2006
13 years 8 months ago
2006
In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...