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An Unsupervised Parameter Grouping Algorithm for Combinatorial Testing
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This article proposes an automatic parameter grouping algorithm for combinatorial testing. First, the normalized mutual information is employed to measure the ...
This article proposes an automatic parameter grouping algorithm for combinatorial testing. ... an unsupervised parameter grouping algorithm for combinatorial ...
Peng Sun, Xiaochuang Tang, Liang Luo: An Unsupervised Parameter Grouping Algorithm for Combinatorial Testing. QRS Companion 2018: 377-381.
7 days ago · The proposed approach is validated through using several data sets and results are compared with those of fuzzy c-means algorithm, particle ...
Mar 3, 2022 · In this work, we study unsupervised Machine Learning approaches for setting these parameters without optimization. We perform clustering with ...
May 6, 2022 · One of these algorithms, the Quantum Approximate Optimization Algorithm stands out as a promising approach to tackling combinatorial problems.
Missing: Grouping | Show results with:Grouping
Oct 29, 2021 · The tests are developed based on an equiv- alence class analysis of the input domain guided by the notion to identify problematic regions of the ...
Missing: Grouping | Show results with:Grouping
This paper presents an approach based on unsupervised learning techniques for the grouping of traces to generate simpler and more understandable models. The ...
(2010) proposed ISAC (Instance-Specific Algorithm Configuration), which first groups the instances into different clusters based on their similarities, and then ...
Abstract—Machine Learning (ML) models could exhibit biased behavior, or algorithmic discrimination, resulting in unfair or discriminatory outcomes.