Efficient dimension reduction algorithm via L_(2,1) norm PCA

Application Research of Computers, pp. 45-47, 2013.

Cited by: 0|Views7

Abstract:

Traditional PCA is sensitive to outliers and feature noises,PCA based on L2,1-norm can improve the problems.Whereas present L2,1-PCA algorithms implement dimension reduction on the rank of the matrix and the rank is complex problem.In order to solve this problem,this paper proposed using trace norm instead of rank,then the calculation of ...More

Code:

Data:

ZH一种基于L_(2,1)范数的PCA维数约简算法
Get fulltext within 24h
Bibtex
Upload PDF

1.Your uploaded documents will be check within 24h, and coins will be credited to your account.

2.As the current system does not support cash withdrawal, you can add staff WeChat (AMxiaomai) to receive it as a red packet.

3.10 coins will be exchanged for 1 yuan.

?

Upload a single paper

for 5 coins

Wechat's Red Packet
?

Upload 50 articles

for 250 coins

Wechat's Red Packet
?

Upload 200 articles

for 1000 coins

Wechat's Red Packet
?

Upload 500 articles

for 2500 coins

Wechat's Red Packet
?

Upload 1000 articles

for 5000 coins

Wechat's Red Packet
Your rating :
0

 

Tags
Comments