Model Selection for Ranking SVM Using Regularization Path
Karina Zapien, Gilles Gasso, Thomas Gärtner, Stéphane Canu · BiblioBoard Library Catalog (Open Research Library) · 2009
Regularization parameter search for the ranking SVM can be efficiently done by calculating the regularization path. This approach calculates efficiently the optimal solution for all possible regularization parameters by solving (in practice) small linear problems. This approach has the advantage of overcoming local minimum of the regularization function. These advantages make the parameter selection considerably less time consuming and the obtained optimal solution for each model more robust.