One of the most exciting recent directions in machine learning is the discovery that the combination of multiple classifiers often results in significantly better performance than...
In this paper we present and discuss the results of a text coherence experiment performed on a small corpus of Romanian text from a number of alternative high school manuals. Duri...
Recently, boosting is used widely in object detection applications because of its impressive performance in both speed and accuracy. However, learning weak classifiers which is on...
In this paper, we report our work on spam filtering with three novel bayesian classification methods: Aggregating One-Dependence Estimators (AODE), Hidden Naïve Bayes (HNB), Loca...
Abstract. We present a new method for voting exponential (in the number of attributes) size sets of Bayesian classifiers in polynomial time with polynomial memory requirements. Tra...