|
Semi-Supervised Bipartite Ranking with the Normalized Rayleigh Coefficient
Liva Ralaivola
In: ESANN 09, 23-25 Apr. 2009, Bruges.
AbstractWe propose a new algorithm for semi-supervised learning in the
bipartite ranking framework. It is based on the maximization of
a so-called normalized Rayleigh coefficient, which differs from
the usual Rayleigh coefficient of Fisher's linear discriminant
in that the actual covariance matrices are used
instead of the scatter matrices. We show that if the class
conditional distributions are Gaussian, then the ranking function
produced by our algorithm is the optimal linear ranking function.
A kernelized version of the proposed algorithm and
a semi-supervised formulation are provided.
Preliminary numerical results are promising. | EPrint Type: | Conference or Workshop Item (Paper) |
|---|
| Project Keyword: | Project Keyword UNSPECIFIED |
|---|
| Subjects: | Theory & Algorithms |
|---|
| ID Code: | 5036 |
|---|
| Deposited By: | Liva Ralaivola |
|---|
| Deposited On: | 24 March 2009 |
|---|
[Edit]
| 