10 Metrics to Evaluate Supervised Machine Learning Models

Supervised machine learning algorithms try to model the relationship between features (independent variables) and a label (target variable) given a set of observations. The two main types of supervised learning tasks are classification and regression. Classification is a supervised learning technique in which the target variable is discrete (or categorical). Consider a bank collecting a dataset that contains several features about their customers such as the number of products, transactions within the last month, expected monthly income, and so on. The bank is trying to predict whether a customer will churn based on this dataset.