A robust correlation analysis framework for imbalanced and dichotomous data with uncertainty
Correlation analysis is one of the fundamental mathematical tools for identifying
dependence between classes. However, the accuracy of the analysis could be jeopardized …
dependence between classes. However, the accuracy of the analysis could be jeopardized …
Does machine learning need fuzzy logic?
E Hüllermeier - Fuzzy Sets and Systems, 2015 - Elsevier
This article is a short position paper in which the author outlines his (necessarily subjective)
perception of current research in fuzzy machine learning, that is, the use of formal concepts …
perception of current research in fuzzy machine learning, that is, the use of formal concepts …
Fuzzy sets in data analysis: From statistical foundations to machine learning
Basic ideas and formal concepts from fuzzy sets and fuzzy logic have been used
successfully in various branches of science and engineering. This paper elaborates on the …
successfully in various branches of science and engineering. This paper elaborates on the …
Vulnerability assessment of urban community and critical infrastructures for integrated flood risk management and climate adaptation strategies
R Espada, A Apan, K McDougall - … of Disaster Resilience in the Built …, 2017 - emerald.com
Purpose The purpose of this paper was to develop an integrated framework for assessing
the flood risk and climate adaptation capacity of an urban area and its critical infrastructures …
the flood risk and climate adaptation capacity of an urban area and its critical infrastructures …
Kendall's rank correlation on quantized data: an interval-valued approach
Kendall's rank correlation coefficient, also called Kendall's τ, is an efficient and robust way
for identifying monotone relationships between two data sequences. However, when …
for identifying monotone relationships between two data sequences. However, when …
Machine Learning and Data Analysis Using Posets: A Survey
AM Mwafise - arXiv preprint arXiv:2404.03082, 2024 - arxiv.org
Posets are discrete mathematical structures which are ubiquitous in a broad range of data
analysis and machine learning applications. Research connecting posets to the data …
analysis and machine learning applications. Research connecting posets to the data …
Testing noisy numerical data for monotonic association
U Bodenhofer, M Krone, F Klawonn - Information Sciences, 2013 - Elsevier
Rank correlation measures are intended to measure to which extent there is a monotonic
association between two observables. While they are mainly designed for ordinal data, they …
association between two observables. While they are mainly designed for ordinal data, they …
[PDF][PDF] On measuring and testing the ordinal correlation between bipolar outranking relations
R Bisdorff - DA2PL'2012 From Multiple Criteria Decision Aid to …, 2012 - orbilu.uni.lu
We generalize Kendall's rank correlation measure τ to valued relations. Motivation for this
work comes from the need to measure the level of approximation that is required when …
work comes from the need to measure the level of approximation that is required when …
Weighting by Tying: A New Approach to Weighted Rank Correlation
S Henzgen, E Hüllermeier - arXiv preprint arXiv:2308.10622, 2023 - arxiv.org
Measures of rank correlation are commonly used in statistics to capture the degree of
concordance between two orderings of the same set of items. Standard measures like …
concordance between two orderings of the same set of items. Standard measures like …
Weighted rank correlation: a flexible approach based on fuzzy order relations
S Henzgen, E Hüllermeier - … PKDD 2015, Porto, Portugal, September 7-11 …, 2015 - Springer
Measures of rank correlation are commonly used in statistics to capture the degree of
concordance between two orderings of the same set of items. Standard measures like …
concordance between two orderings of the same set of items. Standard measures like …