• DocumentCode
    3076872
  • Title

    Intelligible machine learning with malibu

  • Author

    Langlois, Robert E. ; Lu, Hui

  • Author_Institution
    Department of Bioengineering, University of Illinois at Chicago, 60607, USA
  • fYear
    2008
  • fDate
    20-25 Aug. 2008
  • Firstpage
    3795
  • Lastpage
    3798
  • 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
  • Keywords
    Application software; Bioinformatics; Biomedical engineering; Computer languages; Java; Machine learning; Machine learning algorithms; Open source software; Performance evaluation; Reproducibility of results; Algorithms; Artificial Intelligence; Computational Biology; Database Management Systems; Databases, Factual; Humans; Information Storage and Retrieval; Programming Languages; Software; User-Computer Interface;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
  • Conference_Location
    Vancouver, BC
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-1814-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2008.4650035
  • Filename
    4650035