e delle Telecomunicazioni,

Expression-based classification of tumors requires stable, reliable and variance re-duction methods, as DNA microarray data are characterized by low size, high di-mensionality, noise and large biological variability. In order to address the variance and curse of dimensionality problems arising from this difficult task, we propose to apply bagged ensembles of Support Vector Machines (SVM) and feature selec-tion algorithms to the recognition of malignant tissues. Presented results show that bagged ensembles of SVMs are more reliable and achieve equal or better classifica-tion accuracy with respect to single SVMs, whereas feature selection methods can further enhance classification accuracy. Key words: Molecular classification of tumors; DNA microarray; bagging; Suppor