1R (short for One Rule) is a supervised classification algorithm. It was proposed by Robert Holte, and its idea is to create a single rule (or simple rule) based on a single attribute from the dataset to make predictions. In summary: The algorithm analyzes each attribute in the dataset. For each attribute, it generates a simple rule that predicts the class based on the attribute’s values. It calculates the classification error for each rule. Finally, it selects the best rule (the one with the lowest error).
