40 Algorithms Every Programmer Should Know

Understanding classification algorithms

In supervised machine learning, if the target variable is a category variable, the model is categorized as a classifier:

• The target variable is called a label.

• The historical data is called labeled data.

• The production data, which the label needs to be predicted for, is called unlabeled data.

The ability to accurately label unlabeled data using a trained model is the real power of classification algorithms. Classifiers predict labels for unlabeled data to answer a particular business question.

Before we present the details of classification algorithms, let's first present a business problem that we will use as a challenge for classifiers. We will then use six different algorithms to answer the same ...