a measure on how well an attribute will split up the remaining data into disjunct groups
to determine the optimal feature to split upon, the decision tree algorithm calculates the change in entropy that would result from a split on each possible feature.
difference between entropy between before and after split  infogain(f) = entropy(s1)-entropy(s2) =post-pre split