Comparison Performance of Decision Tree Classification Model for Spam Filtering with or without the Recursive Feature Elimination (RFE) Approach
Ahmad Fikri Zulfikar, Dede Supriyadi, Yaya Heryadi, Lukas Lukas · 2019
Spam filters have become an important tool for ISP(Internet service Provider) to address the growing spam in cyberspace. Spam filtering is a program used to detect spam, prevent it and enter users' mailboxes. With the rapid growth of Internet technology, email communication is becoming increasingly important in people's daily lives. In addition, the amount of spam contained in emails has increased considerably in recent years. In this study, the authors will compare the performance of the decision tree classification models using or not using Recursive Feature Elimination (RFE) in spam filtering. The results of this test will be compared with the results of level accuracy, recall, precision, and F1Score using or not using the RFE method. where in the results of this level measurement, the model used can be a reference or solution to filter spam correctly, especially through the use of supervised learning data.