We present an empirical comparison of the AUC performance of seven supervised learning methods: SVMs, neural nets, decision trees, k-nearest neighbor, bagged trees, boosted trees,...
1 In this paper, we introduce and evaluate a low complexity macroblock partition mode decision algorithm for interframe prediction in MPEG-2 to H.264 transcoder. The proposed tools...
When performing concept description, models need to be evaluated both on accuracy and comprehensibility. A comprehensible concept description model should present the most importan...
This paper extends previous work on the Skewing algorithm, a promising approach that allows greedy decision tree induction algorithms to handle problematic functions such as parit...
In this article, we propose a special type of decision tree, called a decision cascade, for binarizing document images. Such images are produced by cameras, resulting in varying de...