Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

11

ICML
2005
IEEE

favoriteEmaildiscussreport

103views Machine Learning» more ICML 2005»

A support vector method for multivariate performance measures

14 years 5 months ago

A support vector method for multivariate performance measures

Download www.cs.cornell.edu

This paper presents a Support Vector Method for optimizing multivariate nonlinear performance measures like the F1score. Taking a multivariate prediction approach, we give an algorithm with which such multivariate SVMs can be trained in polynomial time for large classes of potentially non-linear performance measures, in particular ROCArea and all measures that can be computed from the contingency table. The conventional classification SVM arises as a special case of our method.

Thorsten Joachims

Real-time Traffic

ICML 2005 | Machine Learning | Multivariate Nonlinear Performance | Multivariate Prediction Approach | Non-linear Performance Measures |

claim paper

Related Content

» An Investigation of Feature Models for Music Genre Classification Using the Support Vector...

» Highdimensional support union recovery in multivariate regression

» Multivariate profiling of neurodegenerationassociated changes in a subcellular compartment...

» Rule Extraction from Support Vector Machines Measuring the Explanation Capability Using th...

» Adaptive Concept Drift Detection

» Learning in RegionBased Image Retrieval with Generalized Support Vector Machines

» Hybrid feature selection for gesture recognition using support vector machines

» Tangent Distance Kernels for Support Vector Machines

» Multivariate texture retrieval using the SIRV representation and the geodesic distance

Post Info
More Details (n/a)

Added	17 Nov 2009
Updated	17 Nov 2009
Type	Conference
Year	2005
Where	ICML
Authors	Thorsten Joachims

Comments (0)