A novel adaptive and ensemble based classifier prediction model for the pre diagnosis of lung cancer disease

Abstract

known Data mining aims at discovering knowledge from the underlying data When enormous amount of data are stored in files databases and other repositories it is increasingly important to develop powerful means for analysis and interpretation of such data and for the extraction of interesting knowledge that could help in decisionmaking Data mining tools generally address this problem Every year more than 1500000 people die due to lung cancer This newlinemakes l newlineung cancer one of the major causes of death newlineEarly detection of lung cancer disease is vital for prognosis Several attempts have been made earlier newlinefor early detection with varying levels of success newlineThe disease leaves its impression in most of the patients by its symptoms during the onset and growth stage Certain risk factors like cigarette smoking alcohol usage are to be causative agents of Lung cancer This research focusses on developing a model newline based on predictive data mining ensemble classification approach based on the symptoms and risk factors newline newline