Feature selection and weighting are central problems in pattern recognition and instance-based learning. In this work, we discuss the challenges of constructing and weighting feat...
Kreshna Gopal, Tod D. Romo, James C. Sacchettini, ...
The success of stochastic algorithms is often due to their ability to effectively amplify the performance of search heuristics. This is certainly the case with stochastic sampling ...
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
A hyperheuristic is a high level procedure which searches over a space of low level heuristics rather than directly over the space of problem solutions. The sequence of low level h...
Multiple Species Weighted Voting (MSWV) is a genetics-based machine learning (GBML) system with relatively few parameters that combines N two-class classifiers into an N -class cla...