Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection
Ming-Jie Zhao and Adam Pocock and Gavin Brown and Mikel Lujn

Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection.pdf 706.10kB
Type: Paper
Tags:

Bibtex: 
@article{13:2,author={Gavin Brown and Adam Pocock and Ming-Jie Zhao and Mikel Lujn}, Title={Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection},journal={Journal of Machine Learning Research},volume={13}, url={http://www.jmlr.org/papers/volume13/brown12a/brown12a.pdf}}
No stats to report yet.
Related Torrents
Report
Send Feedback Start
   0.000008
DB Connect
   0.000533
Lookup hash in DB
   0.000430
Get torrent details
   0.000126
Get torrent details, finished
   0.000254
Get authors
   0.000001
Select authors
   0.000201
Parse bibtex
   0.000041
Write header
   0.000238
get stars
   0.000119
home tab
   0.000110
render right panel
   0.000009
render ads
   0.000396
fetch current hosters
   0.000247
Start get stats
   0.000342
End get stats
   0.000002
related datasets
   0.001531
Done