Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...
In this paper we propose a novel spatial associative classifier method based on a multi-relational approach that takes spatial relations into account. Classification is driven by s...
This paper proposes a novel Data Envelopment Analysis (DEA) based approach for model combination. We first prove that for the 2-class classification problems DEA models identify t...
Abstract. Quantitative Association Rule (QAR) mining has been recognized an influential research problem over the last decade due to the popularity of quantitative databases and th...
Commercial relational databases currently store vast amounts of real-world data. The data within these relational repositories are represented by multiple relations, which are int...