Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
Accounting frauds have continuously happened all over the world. This leads to the need of predicting business failures. Statistical methods and machine learning techniques have b...
Shi-Ming Huang, Chih-Fong Tsai, David C. Yen, Yin-...
The class imbalance problem (when one of the classes has much less samples than the others) is of great importance in machine learning, because it corresponds to many critical app...
This paper presents an hybrid adaptive system for induction of forest of trees from data streams. The Ultra Fast Forest Tree system (UFFT) is an incremental algorithm, with consta...
This paper describes a hybrid tagger/parser for French (FrAG), and presents results from ongoing development work, corpus annotation and evaluation. The core of the system is a se...