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We proposed a new approach for gene selection and multi-cancer classification based on step-by-step improvement of classification performance (SSiCP). The SSiCP gene selection algorithms were evaluated over the NCI60 and GCM benchmark datasets, with an accuracy of 96.6% and 95.5% in 10-fold cross validation, respectively. Furthermore, the SSiCP outperformed recently published algorithms when applied to another two multi-cancer data sets. Computational evidence indicated that SSiCP can avoid over fitting effectively. Compared with various gene selection algorithms, the implementation of SSiCP is very simple, and all the computational experiments are repeatable.