Building a Classifier using Random Forests

In the healthcare industry, the data is growing day by day. Many organizations store the records of patients in the form of electronic healthcare records (EHR). These records can be used by the doctor for tasks like diagnosis of diseases, etc. Also to detect a disease early, doctor may use the EHR. To assist the doctor, if an algorithm is provided, which classifies data, it becomes much easier for the doctor to identify patients who are likely to develop a disease. Thus, early detection is one advantage of building such classifiers. Another advantage is that the cost of treating any disease will be reduced. Classifier will help to predict the disease and aid in diagnosis. Here, we propose a classifier which gives predictions once the training has been done.