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Due to the vital role of the aberrant DNA methylation during the disease development such as cancer, the comprehension of its mechanism had become essential in the recent years for early detection and diagnosis. With the advent of the high-throughput technologies, there are still several challenges to achieve the classification process using the DNA methylation data. The high-dimensionality and high-noisiness of the DNA methylation data may lead to the degradation of the prediction accuracy. Thus, it becomes increasingly important in a wide range to employ robust computational tools such as feature selection and extraction methods to extract the informative features amongst thousands of them, and hence improving cancer prediction. By using the DNA methylation degree in promoters and probes regions, this paper aims at predicting cancer with a hybridized approach based on the feature selection and …