IDA - Intelligent Data Analysis Research Group

BibTeX Entry

  file = {mlj.10.pdf},
  category = {ida-publications},
  author = {Ond{\v r}ej Ku{\v z}elka and Filip {\v Z}elezn{\'y}},
  title = {Block-Wise Construction of Tree-like Relational Features with Monotone Reducibility and Redundancy},
  journal = {Machine Learning},
  volume = {83},
  number = {2},
  year = {2011},
  pages = {163--192},
  abstract = {We describe an algorithm for constructing a set of tree-like conjunctive relational features by combining smaller conjunctive blocks. Unlike traditional level-wise approaches which preserve the monotonicity of frequency, our block-wise approach preserves monotonicity of feature reducibility and redundancy, which are important in propositionalization employed in the context of classification learning. With pruning based on these properties, our block-wise approach efficiently scales to features including tens of first-order atoms, far beyond the reach of state-of-the art propositionalization or inductive logic programming systems.},
  vvvs = {1},
  projnum = {13/08012/13133},

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