Evaluation of ensemble methods for diagnosing of valvular heart disease

0957-4174/$ see front matter 2009 Elsevier Ltd. A doi:10.1016/j.eswa.2009.12.085 * Corresponding author. Address: Department o Science, Firat University, Technical Education Faculty E-mail addresses: rdas@firat.edu.tr (R. Das), kseng In this work, we investigate the use of ensemble learning for improving classifiers which is one of the important directions… CONTINUE READING