Machine Learning

, Volume 68, Issue 3, pp 267–276

A note on Platt’s probabilistic outputs for support vector machines

Authors

    • Department of Computer Science and Information EngineeringNational Taiwan University
  • Chih-Jen Lin
    • Department of Computer Science and Information EngineeringNational Taiwan University
  • Ruby C. Weng
    • Department of StatisticsNational Chengchi University
TECHNICAL NOTE

DOI: 10.1007/s10994-007-5018-6

Cite this article as:
Lin, H., Lin, C. & Weng, R.C. Mach Learn (2007) 68: 267. doi:10.1007/s10994-007-5018-6

Abstract

Platt’s probabilistic outputs for Support Vector Machines (Platt, J. in Smola, A., et al. (eds.) Advances in large margin classifiers. Cambridge, 2000) has been popular for applications that require posterior class probabilities. In this note, we propose an improved algorithm that theoretically converges and avoids numerical difficulties. A simple and ready-to-use pseudo code is included.

Keywords

Support vector machinePosterior probability
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© Springer Science+Business Media, LLC 2007