Prediction of Lung Cancer Symptoms using Naive Bayes and J48 Classification Techniques

Cancer is the disease which is most dangerous that leads to death for both men and women. Lung cancer is uncontrollable disease if they affect both lungs. Early diagnosis of lung cancer saves enormous life’s, failing which may lead to another severe problems causing sudden fatal end. The advance detection of cancer is not easier process but if it is detected, it is curable. We analyzed the lung cancer prediction using classification algorithm such as Naive Bayes and J48 algorithm. Initially 100 cancer and non-cancer patients’ data were collected pre-processed and analyzed using a classification algorithm for predicting lung cancer. The dataset have 100 instances and 25 attributes. The main aim of this paper is to provide the advance warning to the users and the performance analysis of the classification algorithms. By using classification algorithms Naïve Bayes and j48 .we are going to analyze the lung cancer. Here both cancer and non cancer patient details are collected for processing and analyzing the data which have different instances and attributes.