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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Nikolaos Chaniotakis,Magdalini Papazoglous of interest for each customer, thus improving the prediction results. The highest average F-score of 0.499 for the considered dataset of 826 Canadian customers was obtained using the Random Forest prediction model which was compared to the Decision Tree, Gradient Boosting Tree, XGBoost, Logistic R

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Niki Nikonanou,Alexandra Bouniase prevention, as well as clustering different snapshots of the same network evolving over time to identify similar patterns or abrupt changes. We test our method in an empirical analysis whose goal is clustering brain connectomes to distinguish between patients affected by schizophrenia and healthy

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Conference proceedings‘‘‘‘‘‘‘‘ 2023es a forum for presenting high-quality theoretical and applied works, and promoting and fostering interdisciplinary research and international cooperation. The intended audience is researchers and practitioners who seek the latest developments and applications in the field of data science and classi

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Classification and Data Science in the Digital Age

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A Topological Clustering of Individuals,nalysis (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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Improving Classification of Documents by Semi-supervised Clustering in a Semantic Space,n improves the average precision of classification by SVMs for the 25 largest classes of Reuters collection for about 5,5% with the same level of average recall in comparison to the basic representation in the vector space model. In the case of classification by logistic regression, representation b