Attribute Ranking Driven Filtering of Decision Rules
In decision rule induction approaches either minimal, complete, or satisfying sets of constituent rules are inferred, with an aim of providing predictive properties while offering descriptive capabilities for the learned concepts. Instead of limiting rules at their induction phase we can also execute post-processing of the set of generated decision rules (whether it is complete or not) by filtering out those that meet some constraints. The paper presents the research on rule filtering while following a ranking of conditional attributes, obtained in the process of sequential forward selection of input features for ANN classifiers.
KeywordsDecision Algorithm Decision Rule DRSA Feature Selection Ranking Rule Filtering ANN Stylometry Authorship Attribution
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