Comparisons of Logistic Regression and Artificial Neural Networks in Lung Cancer Data
Yüksel Öner, Taner Tunç, Erol Eğrioğlu, Yıldız Atasoy · American Journal of Intelligent Systems · 2013
In the recent years, there have been many studies rely on med ical data classification with art ificial neural networks and logistic regression. The logistic regression has been commonly used as a statistical method. The logistic regression is the nonlinear method and the nonlinear optimization methods are used parameter estimation in logistic regression. The logistic regression is the model based approximation, and it is the not data-based approximation. Another classification method is the artificial neural netwo rk which has been commonly used in the literature. There are a lot of kinds of artificial neural network; the feed forward neural networks are generally preferred in the literature. In this study, feed forward artificial neural network and logistic regression are compared by classifying lung cancer data. In the result of application, the satisfied accurate classification percentage is obtained from either method.