Which type of problem is referred to as a classification problem?

A classification problem is characterized by the need to categorize data into distinct classes or groups based on certain features or predictors. This typically involves a qualitative target, where the outcomes are categorical rather than numerical. For instance, problems like identifying whether an email is spam or not, classifying types of animals based on their features, or diagnosing diseases based on symptoms are all examples of classification tasks.

In this context, a qualitative target signifies that the goal is to predict a category, such as "yes" or "no," "spam" or "not spam," or various class labels in a multi-class scenario. The focus is on discerning and classifying data points into these defined categories based on the available predictors.

Quantitative targets, on the other hand, relate to regression problems where the outcome is a continuous numeric value, which is distinct from the nature of classification. Predictors can be either qualitative or quantitative; however, the classification problem specifically hinges on the qualitative nature of the target variable.