正规化(语言学)
判别式
回归
约束(计算机辅助设计)
翻译(生物学)
计算机科学
人工智能
数学
弹性网正则化
基础(线性代数)
最小二乘函数近似
模式识别(心理学)
算法
统计
信使核糖核酸
基因
估计员
化学
生物化学
几何学
作者
Lingfeng Wang,Chunhong Pan
出处
期刊:IEEE transactions on neural networks and learning systems
[Institute of Electrical and Electronics Engineers]
日期:2017-01-25
卷期号:29 (4): 1352-1358
被引量:42
标识
DOI:10.1109/tnnls.2017.2651169
摘要
In this brief, we propose a new groupwise retargeted least squares regression (GReLSR) model for multicategory classification. The main motivation behind GReLSR is to utilize an additional regularization to restrict the translation values of ReLSR, so that they should be similar within same class. By analyzing the regression targets of ReLSR, we propose a new formulation of ReLSR, where the translation values are expressed explicitly. On the basis of the new formulation, discriminative least-squares regression can be regarded as a special case of ReLSR with zero translation values. Moreover, a groupwise constraint is added to ReLSR to form the new GReLSR model. Extensive experiments on various machine leaning data sets illustrate that our method outperforms the current state-of-the-art approaches.
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