Blanket Clusterer: A Tool for Automating the Clustering in Unsupervised Learning
Date Issued
2022
Author(s)
Bogdanoski, Konstantin
Trajanov, Dimitar
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.
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.
Subjects
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