0

I want to compute the mutual information between features and my output variable. I was wondering, what is the best way to set the number of bins for each feature? How should be bins interval ? Does all of them should have same bin size? Here is how my data looks like: 

 A         B            C          D       E
 0.30890524 0.54426331 0.100881953 1.7844281 1.9580541
 0.1037904 0.10647233 0.102095382 0.8488240 0.7763768
 0.10367904 0.147233 0.102095382 0.8488240 0.7763768
 0.331458 0.57973406 0.130334158 1.6350764 1.5585344
 0.15101780 0.2377797 0.150907454 0.8556408 1.0199345
 0.14075664 0.04942940 0.0103453 0.7010386 0.523710
6 0.02547862 0.01841224 0.04950307 0.1694650 0.1293436
 0.31318298 0.123281 0.387902840 1.013703 0.9320006
 0.545757 0.5898526 0.242701313 1.8950583 2.1294465
 0.332576 0.44881516 0.181627835 1.5116738 1.5444081
kjetil b halvorsen
  • 63,378
  • 26
  • 142
  • 467
user51661
  • 91
  • 1
  • 5
  • 2
    [Please don't discretize continuous variables.](http://stats.stackexchange.com/q/104402/1352) (And many other threads on this site.) – Stephan Kolassa Oct 01 '15 at 16:28
  • 1
    then how can I compute mutual information if I don't discritize it ? – user51661 Oct 01 '15 at 17:33
  • See https://stats.stackexchange.com/questions/391123/recommended-mutual-information-estimator-for-continuous-variable, https://stats.stackexchange.com/questions/147401/estimating-mutual-information-using-r, https://www.stat.berkeley.edu/~binyu/summer08/L2P2.pdf – kjetil b halvorsen Aug 01 '20 at 19:01

0 Answers0