In this paper we propose a new weighting scheme to automatically generate weight for features based on the intrinsic of the dataset. The new scheme takes a similar approach as the TFIDF model in the text categorization domain. A hybrid model is formulated, which consists of FF and IGF takes into account of connection numbers, connection types and distribution of observed label classes. The weight generated by ICAC is compared to the frequency of features in the dataset. The result of the comparison showed that the weight is decreasing (negatively) correlated to the frequency of features.