Titlebook: Clusters, Orders, and Trees: Methods and Applications; In Honor of Boris Mi Fuad Aleskerov,Boris Goldengorin,Panos M. Pardalos Book 2014 Sp

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From Separating to Proximal Plane Classifiers: A Reviewescribe different proposals to obtain two proximal planes representing the two classes in the binary classification case. In details, we deal with proximal SVM classification by means of a generalized eigenvalues problem. Furthermore, some regularization techniques are analyzed in order to solve the

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Single or Multiple Consensus for Linear Ordershen voters rank candidates in an elective process or in Preference Aggregation, when individuals or criteria put several orders on the items. Often the consensus order is a median order for Kendall’s distance, but other definitions, more easily computable, can be used. In the following, we tackle th

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Weak Hierarchies: A Central Clustering Structurethem. Any cluster collection turns out to be a .-weak hierarchy for some integer .. Weak hierarchies play a central role in cluster analysis in several aspects: they are defined as the 2-weak hierarchies, so that they not only extend directly the well-known hierarchical structure, but they are also

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Some Observations on Oligarchies, Internal Direct Sums, and Lattice Congruencesemingly disparate disciplines can be examined, proved, and subtle relationships can be discovered among them. Typical applications might involve decision theory when presented with evidence from sources that yield conflicting optimal advice, insights into the internal structure of a finite lattice,

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Selecting the Minkowski Exponent for Intelligent K-Means with Feature Weightingfor a Minkowski metric-based version of K-Means, in each of the following two settings: semi-supervised and unsupervised. This paper presents experimental evidence that solutions found with the proposed approaches are sufficiently close to the optimum.