SVMlight System

An SVMlight System is an SVM-centric classification tool created and managed by Thorsten Joachims (that implements the SVMlight Algorithm).

• AKA: SVMlight.
• Context:
  • It can have SVMlight Parameters, such as:
    • A cost-factor Float Number by which training errors on positive examples outweight errors on negative examples.
  • It requires files in SVMlight File Format.
  • …
• Counter-Example(s):
  • TinySVM System.
  • LIBSVM System.
  • SHOGUN Toolbox.
• See: SVMlight Learning File Format.

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References

• Website: http://svmlight.joachims.org/

2002

• (Joachims, 2002) ⇒ Thorsten Joachims. (2002). “Learning to Classify Text Using Support Vector Machines: Methods, Theory, and Algorithms." Dissertation, Kluwer. ISBN:0-7923-7679-X

2004

• (Hastie et al., 2004) ⇒ Trevor Hastie, Saharon Rosset, Robert Tibshirani, and Ji Zhu. (2004). “The Entire Regularization Path for the Support Vector Machine.” In: The Journal of Machine Learning Research, 5.
  • QUOTE: It seems that the regularization parameter C (or l) is often regarded as a genuine “nuisance” in the community of SVM users. Software packages, such as the widely used SVMlight (Joachims, 1999), provide default settings for C, which are then used without much further exploration. A recent introductory document (Hsu et al., 2003) supporting the LIBSVM package does encourage grid search for C.

1999

• (Joachims, 1999) ⇒ Thorsten Joachims. (1999). “Making large-Scale SVM Learning Practical.” In: Advances in Kernel Methods - Support Vector Learning, Bernhard Schölkopf and C. Burges and Alexander J. Smola (ed.), MIT-Press.

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