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The ID3 (Iterative Dichotomiser 3) decision tree algorithm is a supervised machine learning algorithm used for classification problems. It constructs a decision tree by selecting the attribute with the highest Information Gain at each step. Information Gain is calculated using the concept of entropy, which measures the impurity or randomness in the dataset. The algorithm continues splitting the data until all records belong to the same class or no further attributes are available for splitting. ID3 is simple, interpretable, and widely used in educational and laboratory applications to understand decision tree learning. A real-time example of ID3 is predicting whether a customer will purchase a laptop based on age, income, student __________ ______ ________ _____ _______ ___ ________ _____ _________ ____.
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