A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog ...
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. Howe...
Research in bioinformatics is driven by the experimental data. Current biological databases are populated by vast amounts of experimental data. Machine learning has been widely ap...
In this paper we perform an empirical evaluation of supervised learning on highdimensional data. We evaluate performance on three metrics: accuracy, AUC, and squared loss and stud...
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,...