A Simple Relational Classifier

@misc{citeulike:2200100, abstract = {We analyze a Relational Neighbor (RN) classifier, a simple relational predictive model that predicts only based on class labels of related neighbors, using no learning and no inherent attributes. We show that it performs surprisingly well by comparing it to more complex models such as Probabilistic Relational Models and Relational Probability Trees on three data sets from published work.}, author = {Macskassy, S. and Provost, F. }, citeulike-article-id = {2200100}, keywords = {learning}, posted-at = {2008-03-11 19:47:11}, priority = {2}, title = {A Simple Relational Classifier}, url = {http://citeseer.ist.psu.edu/691435.html}, year = {2003} }

TY - GEN ID - citeulike:2200100 L3 - citeulike-article-id:2200100 TI - A Simple Relational Classifier N2 - We analyze a Relational Neighbor (RN) classifier, a simple relational predictive model that predicts only based on class labels of related neighbors, using no learning and no inherent attributes. We show that it performs surprisingly well by comparing it to more complex models such as Probabilistic Relational Models and Relational Probability Trees on three data sets from published work. KW - learning AU - Macskassy, S AU - Provost, F PY - 2003/// UR - http://citeseer.ist.psu.edu/691435.html ER -