Model of Decision Tree for Email Classification
Abstract: Aside from the undeniable benefits, the advent of the internet has resulted in a number of unfavourable security consequences. Spam emails are one of the most difficult problems that web users face. Spam refers to any and all emails containing unsolicited content that arrive in a user's email box. Spam can frequently cause network congestion and blocking, as well as system damage for receiving and sending electronic messages. As a result, distinguishing between spam and legitimate email has become critical. This paper presents a novel approach to feature selection and the Iterative Dichotomiser 3 (ID3) algorithm for generating a choice tree for email classification. The experimental results show that the proposed model achieves a very high level of accuracy.
Keywords: Email Data Set, Data Pre-Processing, Extraction and Selection of Features, Decision Tree, Spam Detection
How to Cite?: Nallamothu Naveen Kumar, "Model of Decision Tree for Email Classification", Volume 11 Issue 7, July 2022, International Journal of Science and Research (IJSR), Pages: 1502-1505, https://www.ijsr.net/getabstract.php?paperid=SR22722110223, DOI: https://dx.doi.org/10.21275/SR22722110223