Fuzzy clustering techniques have been applied in many varied fields including medicine, geology, and engineering. The Fuzzy c-Means (FCM) algorithm, developed by Dunn and generalized by Bezdek, has been use in pattern recognition, clustering, and feature selection and has been found to be very useful for eliminating subjective interpretation of data from the review process. This paper focuses on finding small number of genes that can best predict the type of cancer. From the samples taken from several groups of individuals with known classes, the group to which a new individual belongs to is determined accurately. The paper uses a classical Fuzzy c-means clustering algorithm for gene selection and classification. The methodology was applied on publicly available cancer databases.

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