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dc.contributor.authorBogdanoski, Konstantinen_US
dc.contributor.authorMishev, Kostadinen_US
dc.contributor.authorTrajanov, Dimitaren_US
dc.date.accessioned2023-08-16T09:35:20Z-
dc.date.available2023-08-16T09:35:20Z-
dc.date.issued2022-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/27434-
dc.description.abstractWe propose a generic hierarchical clustering algorithm - named Blanket Clusterer, which allows researchers to examine their data and verify the results gained from other machine learning techniques. We also integrate a three-dimensional visualization plugin that provides better understanding of the clustering results. We verify the tool on a specific use-case, i.e., measuring the clustering techniques performances on a textual dataset based solely on ICD-9 descriptions encoded using the Word2Vec distributed representations. The verification shows that Blanket Clusterer provides an efficient pipeline for evaluating and interpreting the most frequently used clustering methods in unsupervised learning.en_US
dc.subjectUnsupervised Learning, Clustering, Hierarchical Clustering, Data Visualization, Machine Learning, Algorithm Optimisation, Machine Learning Tools, Blanket Clusterer, Silhouette Scoreen_US
dc.titleBlanket Clusterer: A Tool for Automating the Clustering in Unsupervised Learningen_US
dc.typeProceeding articleen_US
dc.relation.conferenceDeLTA 2022 - 3rd International Conference on Deep Learning Theory and Applicationsen_US
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Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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