Predictive Analytics Model Based on Multiclass Classification for Asthma Severity by Using Random Forest Algorithm

In modern life, health status prediction has become very crucial. Big data analysis plays a vital role to predict this perfectly. Asthma is a severe chronic disease with severe symptoms. Asthma disease is a chronic disease that leads to death. Researchers have focused on this for better decision making to predict the disease timely use of predictive analysis. This study proposes a Predictive Analytic Model for Asthma prediction using Random Forest (PAM-RF). Data of patients suffering from Asthma has been trained by a random forest approach which predicts to classify the data. Experiments are performed on Hadoop-spark which predicts the future health state of patients. The proposed approach has attained an accuracy of 98.80 percent to predict the asthma disease.