Titlebook: Analysis of Large and Complex Data; Adalbert F.X. Wilhelm,Hans A. Kestler Conference proceedings 2016 Springer International Publishing Sw

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Multidimensional Spectra and Number Theoryices, etc. This paper presents a comparison study for clusteringefficiency (according to adjusted Rand index) for spectral, ensemble, and spectral-mean shifted clusteringmethods for symbolic data. Evaluation studies with application of artificial data with known cluster structure (obtained from . an

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Pointwise Dimension for Hyperbolic Dynamicsingand supervised classificationtasks. Motivated by the importance of pre-processing approaches in the traditional clusteringcontext, this paper explores to what extent supervised pre-processing steps could help traditional clusteringto obtain better performance on supervised clusteringtasks. This p

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Quality Feature Space of Transmitted Speech, multivariate random processes; the objects are represented by functions. In this paper we discuss different types of regression model: linear and logistic. Various methods of representing functional data are also examined. The approaches discussed are illustrated with an application to two real dat

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1431-8814 men in July 2014. This conference unites diverse researchers in the pursuit of a common topic, creating truly unique synergies in the process..978-3-319-25224-7978-3-319-25226-1Series ISSN 1431-8814 Series E-ISSN 2198-3321

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Using Annotated Suffix Tree Similarity Measure for Text Summarisationons of the VSM model, such as being dependent on the size of vocabulary, the length of sentences and demanding stemming or lemmatisation. This is achieved by taking all fuzzy matches between sentences into account and computing probabilities of matched concurrencies. For testing the method on Russia

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Quantitative Recurrence and Dimension Theoryaim of this paper is not to provide an exhaustive survey of model selection, but to show the main used criteria in a . mixture setting and how they can be adapted to a . context. In the last decade two criteria based on the observed composite likelihood were introduced. Here, we propose some new ext

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Product Structure of Hyperbolic Measurese MIMLSVM algorithm in combination with the .-Medoids clustering algorithm to transform the Multi-Instance to a Single-Instance representation. For the clusteringdistance measure we consider variants of the Hausdorff distance, namely Median- and Average-Based Hausdorff distance. Finally, active lear