Scheduled Maintenance on March 25th, 2017:
Single article purchases and IEEE account management will be unavailable from 4:00 AM until 6:30 PM (ET). We apologize for the inconvenience.
By Topic

Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
3 Author(s)

We propose a highly efficient framework for kernel multi-class models with a large and structured set of classes. Kernel parameters are learned automatically by maximizing the cross-validation log likelihood, and predictive probabilities are estimated. We demonstrate our approach on large scale text classification tasks with hierarchical class structure, achieving state-of-the-art results in an order of magnitude less time than previous work.