Titlebook: Classification and Data Science in the Digital Age; Paula Brito,José G. Dias,Rebecca Nugent Conference proceedings‘‘‘‘‘‘‘‘ 2023 The Editor

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Improving Classification of Documents by Semi-supervised Clustering in a Semantic Space,ich penalizes clusterings that are distant from classification of training documents given by experts. Reduced .-means (RKM) enables simultaneously clustering of documents and extraction of factors. By projection of documents represented in the vector space model on extracted factors, documents are

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Hemiparesis

FOLLY

Clustering Student Mobility Data in 3-Way Networks, types are linked. The proposed approach enables simplifying a 3-way network into a weighted two-mode network by considering the statistical concept of joint dependence in a multiway contingency table. Starting from a real application on student mobility data in Italian universities, a 3-way network

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Similarity Forest for Time Series Classification,sts, during already 20 years of existence, proved to be one of the most excellent methods, showing top performance across a vast array of domains, preserving simplicity, time efficiency, still being interpretable at the same time. However, its usage is limited to multidimensional data. Similarity fo

LEVY

https://doi.org/10.1007/978-981-13-0671-6nalysis (PCA) or multiple correspondence analysis (MCA), depending on the type of variable, then classifies individuals into homogeneous group, relative to the structure of the variables considered. The proposed TCI method is presented and illustrated here using a real dataset with quantitative vari

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