The SMS Spam Collection is a public set of SMS labeled messages that have been collected for mobile phone spam research. Further details about the sources of the dataset is found in UCI Machine Learning Respository: https://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection#
This model evaluates 5,574 email messages having spam (bad emails) and ham (good email). The goal is to predict spam emails and attention was given to "Precision" during the model validation process, since we have a higher cost/penalty of False Positives (wrongfully classifying a good email as bad/spam email). Different classifiers were used in comparism to see which favors our prediction the most. The name of the dataset is SMSSpamCollection.