The OneR (One Rule) classification model is a simple yet effective rule-based machine learning algorithm. It generates one rule for each feature in the dataset and then selects the rule with the lowest error rate for classification. Despite its simplicity, OneR performs surprisingly well on many classification tasks, often competing with more complex machine learning models.

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