PROPER: Performance visualization for optimizing and comparing ranking classifiers in MATLAB

BACKGROUND: One of the recent challenges of computational biology is development of new algorithms, tools and software to facilitate predictive modeling of big data generated by high-throughput technologies in biomedical research. RESULTS: To meet these demands we developed PROPER - a package for vi...

Descripción completa

Detalles Bibliográficos
Autores principales: Jahandideh, Samad, Sharifi, Fatemeh, Jaroszewski, Lukasz, Godzik, Adam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4668683/
https://www.ncbi.nlm.nih.gov/pubmed/26635892
http://dx.doi.org/10.1186/s13029-015-0047-1
Descripción
Sumario:BACKGROUND: One of the recent challenges of computational biology is development of new algorithms, tools and software to facilitate predictive modeling of big data generated by high-throughput technologies in biomedical research. RESULTS: To meet these demands we developed PROPER - a package for visual evaluation of ranking classifiers for biological big data mining studies in the MATLAB environment. CONCLUSION: PROPER is an efficient tool for optimization and comparison of ranking classifiers, providing over 20 different two- and three-dimensional performance curves. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13029-015-0047-1) contains supplementary material, which is available to authorized users.

Ejemplares similares