Pointwise MI between class c and feature f measures how much information presence of f contains about c: Gain Ratio (GR) is a normalized variant of Information Gain (IG), introduced into machine learning from information theory (Quinlan, 1993).
iG measures the number of bits of information obtained about presence and absence of a class by knowing the presence or absence of the feature 1 : Gain Ratio aims to overcome one disadvantage of iG which is the fact that iG grows not only with the increase of dependence between f and c, but also with the increase of the entropy of f. why features with low entropy receive smaller iG weights although they may be strongly correlated with a class.