We propose a fully Bayesian approach for generalized kernel models (GKMs), which are extensions of generalized linear models in the feature space induced by a reproducing kernel. ...
Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. ...
Background: The relation between software effort and size has been modeled in literature as exponential, in the sense that the natural logarithm of effort is expressed as a linear...
We present a new regression algorithm called Additive Groves and show empirically that it is superior in performance to a number of other established regression methods. A single G...
—Methods for learning decision rules are being successfully applied to many problem domains, especially where understanding and interpretation of the learned model is necessary. ...
Static analysis tools report software defects that may or may not be detected by other verification methods. Two challenges complicating the adoption of these tools are spurious f...
Joseph R. Ruthruff, John Penix, J. David Morgentha...