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

招人嫉妒

Clustering Brain Connectomes Through a Density-Peak Approach,se 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

钻孔

Similarity Forest for Time Series Classification, similarity forest with 1-nearest neighbor and random forest on the UCR (University of California, Riverside) benchmark database.We show that similarity forest with DTW, taking into account mean ranks, outperforms other classifiers. The comparison is enriched with statistical analysis.

ovation

愤慨一下

1431-8814 and real-world applications in different areas.Benefits res.The contributions gathered in this open access book focus on modern methods for data science and classification and present a series of real-world applications. Numerous research topics are covered, ranging from statistical inference and m

抓住他投降

AMOR

Research on e-Learning and ICT in Educationterconnected by-pass fraud. This is a real-world problem from high-speed telecommunications data that clearly illustrates the need for online data stream processing. In the second study, we present an optimization algorithm for online hyper-parameter tuning from nonstationary data streams.

engender

frenzy

exostosis

BRUNT

Kleopatra Nikolopoulou,Vasilis Gialamasrix. In order to cluster the . units in . groups, the spectral clustering application to three-way data can be a powerful tool for unsupervised classification. Here, one example on real three-way data have been presented showing that spectral clustering method is a competitive method to cluster this type of data.