Application of Random Forest in Various Fields as the Most Reliable and Effective Data Mining Technique

This paper reviews the work done in various papers in the field of random forest to emphasize its importance as an important data analysis algorithm while comparing it with other algorithm at some places and sometimes using the algorithm with other methods for better accuracy at tree learning. It also studies the practical experiments done to establish the superiority of random forest over other algorithms and thus suggests extending its use in other important sectors where it has not yet been implemented. The use of random forest in the field of analyzing student performance, predicting financial crisis in business and predicting disease risk from highly imbalanced data has been studied here which will give an outline on how it will work for other fields in which its use will be suggested.