In the proposed EFC (Explainable Feature Construction) system, we construct various types of features: operator-based features (using logical, relational, Cartesian, and numerical operators), features from rule learning (Hühn and Hüllermeier, 2009), and features based on a threshold for the presence of several features ...
3 Explanation-based Feature Construction. In classical EBL, an “explanation” is a logical proof that shows how the class label of a particular labeled ...
This work describes an approach to feature construction where task-relevant discriminative features are automatically constructed, ...
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We describe an approach to feature construction where task-relevant discriminative features are automatically constructed, guided by an explanation-based ...
We describe an approach to feature construction where task-relevant discriminative features are automatically constructed, guided by an explanation-based ...
Jan 23, 2023 · The proposed Explainable Feature Construction (EFC) methodology identifies groups of co- occurring attributes exposed by popular explanation ...
TL;DR: This work describes an approach to feature construction where task-relevant discriminative features are automatically constructed, ...
We propose a genetic algorithm based method to construct interpretable features for industrial modeling in this paper.
Explanation Based Feature Construction Shiau Hong Lim Compatibility with Devices. Explanation Based Feature Construction Shiau Hong Lim Enhanced eBook Features.
Feature construction (aka constructive induction or attribute discovery) adds derived features to data in order to improve learning effectiveness.