On the Lattice of Conceptual Measurements
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Abstract (arXiv)
We present a novel approach for data set scaling based on scale-measures from formal concept analysis, i.e., continuous maps between closure systems, and derive a canonical representation. Moreover, we prove said scale-measures are lattice ordered with respect to the closure systems. This enables exploring the set of scale-measures through by the use of meet and join operations. Furthermore we show that the lattice of scale-measures is isomorphic to the lattice of sub-closure systems that arises from the original data. Finally, we provide another representation of scale-measures using propositional logic in terms of data set features. Our theoretical findings are discussed by means of examples.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Dec 2020.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 4; 2024: 1.
8 papers.
- 2021Quantifying the Conceptual Error in Dimensionality Reductioncited by 6
- 2023Conceptual Views on Tree Ensemble Classifierscited by 3
- 2021Exploring Scale-Measures of Data Setscited by 2
- 2023Scaling Dimensioncited by 2
- 2023Ordinal Motifs in Latticescited by 2
- 2023Automatic Textual Explanations of Concept Latticescited by 2
- 2022Conceptual Views of Neural Networks: A Framework for Neuro-Symbolic Analysiscited by 1
- 2024The Geometric Structure of Topic Modelscited by 1
- 2024The Geometric Structure of Topic Models6 Mar 2024
- 2023Automatic Textual Explanations of Concept Lattices17 Apr 2023
- 2023Ordinal Motifs in Lattices10 Apr 2023
- 2023Scaling Dimension17 Feb 2023
- 2023Conceptual Views on Tree Ensemble Classifiers10 Feb 2023
- 2022Conceptual Views of Neural Networks: A Framework for Neuro-Symbolic Analysis27 Sep 2022
- 2021Quantifying the Conceptual Error in Dimensionality Reduction12 Jun 2021
- 2021Exploring Scale-Measures of Data Sets4 Feb 2021