Spam email detection is basically a machine learning classification problem. Let's get started by learning important concepts of machine learning classification. Classification is one of the main instances of supervised learning. Given a training set of data containing observations and their associated categorical outputs, the goal of classification is to learn a general rule that correctly maps the observations (also called features or predictive variables) to the target categories (also called labels or classes). Put another way, a trained classification model will be generated after learning from features and targets of training samples, as shown in the first half of the following diagram. When new or unseen data comes in, the trained model will be able to determine their desired memberships. Class information will be predicted based on the known input features using the trained classification model, as displayed in the second half of the following diagram: