Growing Simpler Decision Trees to Facilitate Knowledge Discovery

  title={Growing Simpler Decision Trees to Facilitate Knowledge Discovery},
  author={Kevin J. Cherkauer and Jude W. Shavlik},
When using machine learning techniques for knowledge discovery, output that is comprehensible to a human is as important as predictive accuracy. We introduce a new algorithm, SET-Gen, that improves the comprehensibility of decision trees grown by standard C4.5 without reducing accuracy. It does this by using genetic search to select the set of input features C4.5 is allowed to use to build its tree. We test SET-Gen on a wide variety of real-world datasets and show that SET-Gen trees are… CONTINUE READING

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