Cancer is caused by mutations in the genes of a cell. A cancer tumor can have thousands of genetic mutations of which some contribute to growth of the tumor and others do not. Clinicians interpret the genetic mutations and manually classify them on the basis of evidence from clinical literature which is extremely time consuming. We have developed a data learning algorithm using data which contains thousands of mutations manually annotated by researchers and oncologists which classifies genetic variations into nine categories.