2015
DOI: 10.1016/j.chemolab.2015.06.005
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Weighted power–weakness ratio for multi-criteria decision making

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Cited by 14 publications
(12 citation statements)
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“…This preliminary result fully justifies the introduction of the adjunct dissimilarity factor that improves the classification performance in about 50% of the analyzed cases. [49] for multi-criteria decision-making and ranking comparison.…”
Section: General Analysismentioning
confidence: 99%
See 1 more Smart Citation
“…This preliminary result fully justifies the introduction of the adjunct dissimilarity factor that improves the classification performance in about 50% of the analyzed cases. [49] for multi-criteria decision-making and ranking comparison.…”
Section: General Analysismentioning
confidence: 99%
“…wPWR is based on pairwise comparisons between objects and it has already been applied to address several issues, such as model comparison, hazardous compounds ranking, virtual screening and partial ordering [49]- [51]. The core of wPWR is the generation of the so-called tournament table (T), which summarizes the pairwise comparisons between the objects in a win-loss manner.…”
Section: General Analysismentioning
confidence: 99%
“…Finally, if the values are equal (x ik ≜ x jk ), the two objects "tie the comparison" for the kth criterion and half a credit is given to both. This weighting scheme was already introduced in our previous work [5], as it is a very simple and efficient way to weight criteria and compare objects. Note that all the values of T W range from 0 to 1…”
Section: Weighted Regularized Hasse Theorymentioning
confidence: 99%
“…In this work, in particular, for each data set, we calculated the ranks from Copeland-like scores of (a) all the matrices of the H R family, (b) the original Hasse (HH), and (c) the weighted count matrix T W (Cop). For the sake of comparison, also wPWR ranks were taken into account since they derive from an eigenvector-eigenvalue decomposition of T W [5]. In this way, for each data set, each of the n objects was described by T + 3 ranks obtained by the approaches listed above, where T is the number of the H R family.…”
Section: Statistics and Multivariate Analysismentioning
confidence: 99%
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