We study cost-sensitive learning of decision trees that incorporate both test costs and misclassification costs. In particular, we first propose a lazy decision tree learning that ...
Gene prediction is one of the most challenging tasks in genome analysis, for which many tools have been developed and are still evolving. In this paper, we present a novel gene pr...
Rong She, Jeffrey Shih-Chieh Chu, Ke Wang, Nanshen...
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
This paper explores the application of the Minimum Description Length principle for pruning decision trees. We present a new algorithm that intuitively captures the primary goal o...
The Basel New Accord which is being implemented throughout the banking world on 1 January 2007 has made a significant difference to the use of modelling within financial organisat...