Text Classification (or Text Categorization) is a popular machine learning task which consists in assigning categories to documents. Feature weight methods are classic tools that are used in text categorization in order to assign a score to each term of a document based on a mathematical formula. In this paper, we are interested in automatically generating these formulas based on genetic programming. We experiment the generated formulas on three well-known benchmarks and state of the art classifiers.