Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
Jennifer Neville, Brian Gallagher, Tina Eliassi-Ra...
We present an improved bound on the difference between training and test errors for voting classifiers. This improved averaging bound provides a theoretical justification for popu...
Smaller input data sets such as the test and the train input sets are commonly used in simulation to estimate the impact of architecture/micro-architecture features on the perform...
Wei-Chung Hsu, Howard Chen, Pen-Chung Yew, Dong-yu...
Often a rule-based system is tested by checking its performance on a number of test cases with known solutions, modifying the system until it gives the correct results for all or ...
We propose a new method for comparing learning algorithms on multiple tasks which is based on a novel non-parametric test that we call the Poisson binomial test. The key aspect of...