Can anyone explain me the fisher score working
From Feature Selection for Classification: A Review (Jiliang Tang, Salem Alelyani and Huan Liu)


  Fisher Score: Features with high quality should assign similar values to instances
  in the same class and different values to instances from different
  classes.


From Generalized Fisher Score for Feature Selection (Quanquan Gu, Zhenhui Li, Jiawei Han)


  Fisher Score: The key idea of Fisher score is to find a subset of features, 
  such that in the data space spanned by the selected
  features, the distances between data points in different classes are
  as large as possible, while the distances between data points in the
  same class are as small as possible.


If you are interested in the mathematical explanation, I would suggest the second paper, on section 2 (A Brief Review of Fisher Score)