We developed an approach to two-way classification based on the χ2 distance and Correspondence Analysis. We present, in particular, two classification algorithms: the first one operates a dimension reduction before applying clustering techniques to rows and columns. The second one, successively partitions the data matrix to extract several classification schemes rather than one. Applications to gene expression and web data are presented. The results are compared with an optimal partition algorithm.