Abstract
Decision trees are a popular class of machine learning methods. Taking binary classification as an example, we can regard the task as deciding the answer to the question Is this instance positive? As the name suggests, a decision tree makes decisions based on tree structures, which is also a common decision-making mechanism used by humans. For example, in order to answer the question Is this watermelon ripe? we usually go through a series of judgments or sub-decisions: we first consider What is the color? If it is green then What is the shape of root? If it is curly then What is the knocking sound? Finally, based on the observations, we decide whether the watermelon is ripe or not. Such a decision process is illustrated in Figure 4.1.
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Zhou, ZH. (2021). Decision Trees. In: Machine Learning. Springer, Singapore. https://doi.org/10.1007/978-981-15-1967-3_4
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DOI: https://doi.org/10.1007/978-981-15-1967-3_4
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