Titlebook: Intelligent Information and Database Systems; 14th Asian Conferenc Ngoc Thanh Nguyen,Tien Khoa Tran,Edward Szczerbick Conference proceeding

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0302-9743 tional imaging and vision, decision support and control systems, and data modeling and processing for industry 4.0. The accepted and presented papers focus on new trends and challenges facing the intelligent information and database systems community..978-3-031-21966-5978-3-031-21967-2Series ISSN 0302-9743 Series E-ISSN 1611-3349

indigenous

Covariance Controlled Bayesian Rose Treesevel as a function of likelihood. The developed method allows maximising customisation possibilities and comparative analysis between the nature of clusters. It can be applied to the clustering of different types of content, e.g. visual, textual, or in a modern approach to the construction of container databases.

Palatial

Aggregated Performance Measures for Multi-class Classificationhought of as an analogue of classical ones. The proposed measures better represent the multinomial nature of such algorithms and obtain more valuable information that allows selecting the correct direction while analysing the gradient of the resulting measures.

carotid-bruit

Frisky

Pastry

stress-test

Lumbar-Stenosis

Graph Neural Networks-Based Multilabel Classification of Citation Networkhis context, many authors have recently proposed to adapt existing approaches to graphs and networks. In this paper we train three models of Graph Neural Networks on an academic citation network of Computer Science papers, and we explore the advantages of turning the problem into a multilabel classification problem.

Small-Intestine

Parameter Distribution Ensemble Learning for Sudden Concept Drift Detectiontance of a data stream is a concept drift point or not. The experimental results on the synthetic and classic real-world streaming datasets showed that the proposed method is much more precise and more sensitive (shown in F1-score, precision, and recall metrics) than the original ERICS models in detecting concept drift, especially a sudden drift.

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