A Finite Newton Method for Classi cation Problems

dc.contributor.authorMangasarian, Olvi
dc.date.accessioned2013-01-17T17:36:46Z
dc.date.available2013-01-17T17:36:46Z
dc.date.issued2001
dc.description.abstractA fundamental classi cation problem of data mining and machine learning is that of minimizing a strongly convex, piecewise quadratic function on the n-dimensional real space Rn. We show nite termination of a Newton method to the unique global solution starting from any point in Rn. If the function is well conditioned, then no stepsize is required from the start, and if not, an Armijo stepsize is used. In either case nite termination is guaranteed to the unique global minimum solution.en
dc.identifier.citation01-11en
dc.identifier.urihttp://digital.library.wisc.edu/1793/64312
dc.subjectNewton methoden
dc.titleA Finite Newton Method for Classi cation Problemsen
dc.typeTechnical Reporten

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
01-11.pdf
Size:
139.83 KB
Format:
Adobe Portable Document Format
Description:
A Finite Newton Method for Classi cation Problems

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
2.03 KB
Format:
Item-specific license agreed upon to submission
Description: