in ML, a feature is data used as an input signal to a predictive model. For example, if a credit card company is trying to predict whether a transaction is fraudulent, a useful feature might be whether the transaction is happening in a foreign country, or how the size of this transaction compares to the customer’s typical transaction. When we refer to a feature, we’re usually referring to the concept of that signal (e.g. “transaction_in_foreign_country”), not a specific value of the feature (e.g. not “transaction #1364 was in a foreign country”).