Abstract
This chapter introduces the TDIDT (Top-Down Induction of Decision Trees) algorithm for inducing classification rules via the intermediate representation of a decision tree. The algorithm can always be applied provided the ‘adequacy condition’ holds for the instances in the training set. The chapter ends by distinguishing three types of reasoning: deduction, abduction and induction.
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References
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Quinlan, J. R. (1986). Induction of decision trees. Machine Learning, 1, 81–106.
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Bramer, M. (2013). Using Decision Trees for Classification. In: Principles of Data Mining. Undergraduate Topics in Computer Science. Springer, London. https://doi.org/10.1007/978-1-4471-4884-5_4
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DOI: https://doi.org/10.1007/978-1-4471-4884-5_4
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