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In recent days, the identified genes which are detecting cancer-causing diseases are plays a crucial part in the microarray data analysis. Huge volume of data required since the disease changed often. Conventional data mining techniques are lacking in space concern and time complexity. Based on big data the proposed work is executed. Using the ISPCA - Improved Supervised Principal Component Analysis, feature extraction is developed in this study. For gene expression, co-variance matrix is generated and through feature selection cancer cl

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