3.txt

This complete matlab for neural network

发信人: GzLi (笑梨), 信区: DataMining
标  题:  Machine Learning 47(2/3) <3>
发信站: 南京大学小百合站 (Thu Jul 18 00:45:19 2002), 站内信件
篇名： On the Learnability and Design of Output Codes for Multiclass Problems
 
刊名： Machine Learning 
ISSN： 0885-6125 
卷期： 47 卷 2/3 期 出版日期： 200205/06  
页码： 从 201 页到 233 页共 33 页 
作者： Crammer Koby   School of Computer Science & Engineering, The Hebrew
 University, Jerusalem 91904, Israel. [e-mail] http://cs.huji
.ac.il/~kobics
 
Singer Yoram   School of Computer Science & Engineering, The Hebrew University
, Jerusalem 91904, Israel. [e-mail] http://cs.huji.ac.il/~singer

 
 
文摘： 
Output coding is a general framework for solving multiclass categorization
 problems. Previous research on output codes has focused on building multiclass
 machines given predefined output codes. In this paper we discuss for the
 first time the problem of designing output codes for multiclass problems
. For the design problem of discrete codes, which have been used extensively
 in previous works, we present mostly negative results. We then introduce
 the notion of continuous codes and cast the design problem of continuous
 codes as a constrained optimization problem. We describe three optimization
 problems corresponding to three different norms of the code matrix. Interest
ingly
, for the l_2 norm our formalism results in a quadratic program whose dual
 does not depend on the length of the code. A special case of our formalism
 provides a multiclass scheme for building support vector machines which 
can be solved efficiently. We give a time and space efficient algorithm for
 solving the quadratic program. We describe preliminary experiments with 
synthetic data show that our algorithm is often two orders of magnitude faster
 than standard quadratic programming packages. We conclude with the generaliz
ation
 properties of the algorithm.
 
 


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※ 修改:．GzLi 于 Jul 18 00:47:22 修改本文．[FROM: 211.80.38.29]
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