AAAI-2019-AFS

KO | EN

gitlite — search

#react #ai #typescript #llm #golang #machine-learning #rust #nodejs #macos #awesome #kubernetes #vue #ios #mcp

(★ 47)

The code of the AAAI-19 paper "AFS: An Attention-based mechanism for Supervised Feature Selection".

AAAI-2019-AFS Latest Version Download

Download Latest Version (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# AAAI-2019-AFS
The code of the AAAI-19 paper "AFS: An Attention-based mechanism for Supervised Feature Selection".
 * AFS.py:the main implementation of the proposed approach AFS
 * run_AFS: gives an example to show the full proceduce of training and evaluating the proposed approach AFS  
 
The datasets used in the experiment:
 * 1 http://yann.lecun.com/exdb/mnist/
 * 2 http://csc.lsu.edu/~saikat/n-mnist/
 * 3 http://featureselection.asu.edu  
 
 
 ## About download
 Because data is a large folder, which include three large files. So you can not download this folder directly. Please follow the instructions below to download data folder.  
 1.Click on the data folder.  
 
 2.Click on the file you want to download, such as mnist_rc.npz.  
 
 3.Click on 'download' in the top right corner.  
 ## Run an example
```
 python main.py  
```  
   
```
@inproceeding{  
  title     = {AFS: An Attention-based mechanism for Supervised Feature Selection},

author    = {Ning Gui, Danni Ge, Ziyin Hu},

booktitle = {Proceedings of the Thirty-Third {AAAI} Conference on Artificial Intelligence,  
             January 27-February 1, 2019, Hilton Hawaiian Village, Honolulu, Hawaii, {USA.}},

year      = {2019}  
}
```

AAAI-2019-AFS

AAAI-2019-AFS Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

AAAI-2019-AFS

AAAI-2019-AFS Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Download README