Hierarchical learning in polynomial Support Vector Machines

Details Hierarchical learning in polynomial Support Vector Machines Hierarchical learning in polynomial Support Vector Machines

2000-10-26

arxiv.org/abs/cond-mat/0010423v1

Physics

Condensed Matter

Disordered Systems and Neural Networks

22 pages, 7 figures, submitted to Machine Learning

Scientific paper

We study the typical properties of polynomial Support Vector Machines within
a Statistical Mechanics approach that allows us to analyze the effect of
different normalizations of the features. If the normalization is adecuately
chosen, there is a hierarchical learning of features of increasing order as a
function of the training set size.

Affiliated with

Also associated with

No associations

Rating

Hierarchical learning in polynomial Support Vector Machines does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Hierarchical learning in polynomial Support Vector Machines, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Hierarchical learning in polynomial Support Vector Machines will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-259748