An evaluation of using ensembles of classifiers for predictions based on genomic and proteomic data
- Computational Biology and Biological Physics
We investigated if combining classifiers into ensembles improved classification performance compared to single classifiers. A couple of commonly used classifiers, nearest centroid classifier and support vector machine, were evaluated using four publicly available data sets. We found ensemble methods generally performed better
than corresponding single classifiers.
- Biochemistry and Molecular Biology
- Other Physics Topics