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}}

Send Feedback Start
   0.000006
DB Connect
   0.000422
Lookup hash in DB
   0.000658
Get torrent details
   0.000606
Get torrent details, finished
   0.000641
Get authors
   0.000006
Select authors
   0.000498
Parse bibtex
   0.000121
Write header
   0.000799
get stars
   0.000405
home tab
   0.000424
render right panel
   0.000011
render ads
   0.000053
fetch current hosters
   0.000660
Done