Information diffusion, viral marketing, and collective classification all attempt to model and exploit the relationships in a network to make inferences about the labels of nodes....
This paper presents ACE (Autonomous Classification Engine), a framework for using and optimizing classifiers. Given a set of feature vectors, ACE experiments with a variety of cla...
Cory McKay, Rebecca Fiebrink, Daniel McEnnis, Bein...
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 ...
The generation of a set of rules underlying a classification problem is performed by applying a new algorithm, called Hamming Clustering (HC). It reconstructs the and-or expressio...
Boosted one-versus-all (OVA) classifiers are commonly used in multiclass problems, such as generic object recognition, biometrics-based identification, or gesture recognition. Join...
Alexandra Stefan (University of Texas at Arlington...