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

Samad Jahandideh; Fatemeh Sharifi; Lukasz Jaroszewski; Adam Godzik

doi:10.1186/s13029-015-0047-1

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

Source Code Biol Med. 2015 Dec 3:10:15. doi: 10.1186/s13029-015-0047-1. eCollection 2015.

Authors

Samad Jahandideh¹, Fatemeh Sharifi², Lukasz Jaroszewski¹, Adam Godzik¹

Affiliations

¹ Bioinformatics and Systems Biology Program, Sanford Burnham Prebys Medical Discovery Institute, 10901 N Torrey Pines Rd, La Jolla, CA 92307 USA.
² Division of Computer Science, School of Informatics and Computing, Indiana University, Bloomington, IN 47405 USA.

Abstract

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.

Keywords: Big data; Predictive modeling; Scoring classifier; Structural genomics.

Abstract

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