1) You must include both your report, source codes, necessary data files and optionally presentation. 2) student is required to submit a report of approximately 2,000-2,500 words along with exhibits to support findings with respect to the provided spam and non-spam messages. This report should consist of: •Overview of classifiers and evaluation metrics •Construction of data sets, identification of features and the process of conducting classification •Technical findings of experiment results •Justified discussion of the performance evaluation outcomes for different classifiers. 3) With respect to each classifier and performance evaluation metrics, you are advised to identify and cite at least one paper published by ACM and IEEE journals or conference proceeding. 4) Technical demonstration chapter which consists of fully explained screenshots when your experiments were conducted in R. That is, you should explain each step of the procedure of classification, and the performance results for your classifiers. 5) you should compare the performance results in terms of evaluation metrics, e.g., accuracy, false positive, recall, F-measure, speed and so on, for the selected classifiers and datasets. 6) A bibliography list of all cited papers and other resources. You must use in-t