Multiple Cancer's Prediction using Hybrid Naïve Baye's Classifier

Cancer is the word which may cause the fear all over the world by its effects. The healthcare industries have large amount of data regarding cancer disease. But to mine the data set and discover the knowledge from the available data is the challenging task in medical diagnosis. In this work, we proposes a novel approach for predicting cancer using hierarchical data mining techniques, namely, Decision Trees, Naïve Bayes and Neural Network. By using all these in a effective manner provide a better and accurate diagnosis results. With the use of basic details as attributes for data set like age, sex, blood pressure and blood sugar level. With the availability of these data, system can predict the likelihood of patients getting a cancer disease