HTILDE: scaling up relational decision trees for very large databases

  title={HTILDE: scaling up relational decision trees for very large databases},
  author={Carina Lopes and Gerson Zaverucha},
Nowadays, many organizations have relational databases with millions of records and an important question is how to extract information from them. This work proposes HTILDE (Hoeffding TILDE) to handle very large relational databases, based on the Inductive Logic Programming (ILP) system TILDE (Top-down Induction of Logical Decision Trees) and the propositional Very Fast Decision Tree (VFDT) learner. It is an incremental and anytime algorithm that uses the Hoeffding bound to find out the amount… CONTINUE READING
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