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Classifiers serve as tools for classifying data into classes. They directly or indirectly take a distribution of data points around a given query point into account. To express the distribution of points from the viewpoint of distances from a given point, a probability distribution mapping...
A new projection-pursuit index is used to identify clusters and other structures in multivariate data. It is obtained from the variance decompositions of the data’s one-dimensional projections, without assuming a model for the data or that the number of clusters is known. The index is affine...
The additive biclustering model for two-way two-mode object by variable data implies overlapping clusterings of both the objects and the variables together with a weight for each bicluster (i.e., a pair of an object and a variable cluster). In the data analysis, an additive biclustering model is...
Mokken scale analysis uses an automated bottom-up stepwise item selection procedure that suffers from two problems. First, when selected during the procedure items satisfy the scaling conditions but they may fail to do so after the scale has been completed. Second, the procedure is approximate...
This paper focuses on combining association measures using corresponding receiver operating characteristic curves. The approach is motivated by a problem of automatic bigram collocation extraction from the field of computational linguistics. It is based on supervised machine learning techniques...
A Thurstonian model for ranks is introduced in which rank-induced dependencies are specified through correlation coefficients among ranked objects that are determined by a vector of rank-induced parameters. The ranking model can be expressed in terms of univariate normal distribution functions,...
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