We propose a new decision tree algorithm, Class Confidence Proportion Decision Tree (CCPDT), which is robust and insensitive to class distribution and generates rules which are st...
Wei Liu, Sanjay Chawla, David A. Cieslak, Nitesh V...
Discovering accurate and interesting classification rules is a significant task in the post-processing stage of a data mining (DM) process. Therefore, an optimization problem exis...
Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP i...
Abstract-- Topology discovery systems are starting to be introduced in the form of easily and widely deployed software. Unfortunately, the research community has not examined the p...
Benoit Donnet, Philippe Raoult, Timur Friedman, Ma...
—The non-data components of a visualization, such as axes and legends, can often be just as important as the data itself. They provide contextual information essential to interpr...