title: Intelligible machine learning with malibu.
abstract: malibu is an open-source machine learning work-bench developed in C/C++ for high-performance real-world applications, namely bioinformatics and medical informatics. It leverages third-party machine learning implementations for more robust bug-free software. This workbench handles several well-studied supervised machine learning problems including classification, regression, importance-weighted classification and multiple-instance learning. The malibu interface was designed to create reproducible experiments ideally run in a remote and/or command line environment. The software can be found at: http://proteomics.bioengr. uic.edu/malibu/index.html.
authors.affiliation: Department of Bioengineering, University of Illinois at Chicago, IL 60607, USA. ezra@uic.edu
authors.forename: Robert E
authors.initials: RE
authors.lastname: Langlois
authors.forename: Hui
authors.initials: H
authors.lastname: Lu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D019295:Computational Biology / Q000379:methods*; D003628:Database Management Systems; D016208:Databases, Factual; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D011381:Programming Languages; D012984:Software; D014584:User-Computer Interface