Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/27434
Title: | Blanket Clusterer: A Tool for Automating the Clustering in Unsupervised Learning | Authors: | Bogdanoski, Konstantin Mishev, Kostadin Trajanov, Dimitar |
Keywords: | Unsupervised Learning, Clustering, Hierarchical Clustering, Data Visualization, Machine Learning, Algorithm Optimisation, Machine Learning Tools, Blanket Clusterer, Silhouette Score | Issue Date: | 2022 | Conference: | DeLTA 2022 - 3rd International Conference on Deep Learning Theory and Applications | Abstract: | We 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. | URI: | http://hdl.handle.net/20.500.12188/27434 |
Appears in Collections: | Faculty of Computer Science and Engineering: Conference papers |
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112760.pdf | 2.06 MB | Adobe PDF | View/Open |
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