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Block-Wise Construction of Tree-like Relational Features with Monotone Reducibility and Redundancy

Ondrej Kuzelka, Filip Zelezný
MLJ 2011 pp. 163-192
doi:10.1007/S10994-010-5208-5 /mlj/2011/kuzelka2011mlj-blockwise/

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.

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Text

Kuzelka and Zelezný. "Block-Wise Construction of Tree-like Relational Features with Monotone Reducibility and Redundancy." Machine Learning, 2011. doi:10.1007/S10994-010-5208-5

Markdown

[Kuzelka and Zelezný. "Block-Wise Construction of Tree-like Relational Features with Monotone Reducibility and Redundancy." Machine Learning, 2011.](https://mlanthology.org/mlj/2011/kuzelka2011mlj-blockwise/) doi:10.1007/S10994-010-5208-5

BibTeX

@article{kuzelka2011mlj-blockwise,
  title     = {{Block-Wise Construction of Tree-like Relational Features with Monotone Reducibility and Redundancy}},
  author    = {Kuzelka, Ondrej and Zelezný, Filip},
  journal   = {Machine Learning},
  year      = {2011},
  pages     = {163-192},
  doi       = {10.1007/S10994-010-5208-5},
  volume    = {83},
  url       = {https://mlanthology.org/mlj/2011/kuzelka2011mlj-blockwise/}
}