Computational diagnosis of cancer is a classification problem, and it has two special requirements on a learning algorithm: perfect accuracy and small number of features used in t...
Naïve Bayes is a well-known effective and efficient classification algorithm, but its probability estimation performance is poor. Averaged One-Dependence Estimators, simply AODE,...
Automatic relevance determination (ARD) and the closely-related sparse Bayesian learning (SBL) framework are effective tools for pruning large numbers of irrelevant features leadi...
Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) o...
Allison Gehrke, Shaojun Sun, Lukasz A. Kurgan, Nat...
Background: Many important high throughput projects use in situ hybridization and may require the analysis of images of spatial cross sections of organisms taken with cellular lev...
Manjunatha Jagalur, Chris Pal, Erik G. Learned-Mil...