Large-scale Linear RankSVM

碩士 === 國立臺灣大學 === 資訊工程學研究所 === 101 === Linear rankSVM is one of the widely used methods for learning to rank. Although its performance may be inferior to nonlinear methods such as kernel rankSVM and gradient boosting decision trees, linear rankSVM is useful to quickly produce a baseline model. Furth...

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Bibliographic Details
Main Authors: Ching-Pei Lee, 李靜沛
Other Authors: Chih-Jen Lin
Format: Others
Language:en_US
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/95333963386449972611