Data mining is process of extracting valuable and meaningful information from the large data set. There are many techniques but most important are classification and regression. In this paper we are discuss about classification algorithm i.e. Random Forest and Genetic Algorithm is for the optimization purpose. Random Forest is multi-classifier and it is used for increasing the accuracy of the classifier. RF constructs many decision trees from the given data set and it picks result of that classifier which is more accurate. In this paper we are combining both the algorithm i.e. Random Forest and Genetic Algorithm for more optimized result and to increase the accuracy of the classifier. So the class predicated by the different classifier in Random forest is provided to the genetic algorithm and then genetic algorithm gives the most accurate result from the given predicated result.
Big Data, Random Forest, Genetic Algorithm, De-identification policies
