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Evaluation of Approximate Hierarchical Clustering Algorithms

Thesis type
  • Bachelor
Status Cancelled
  • Prof. Dr. Martin Reißel

There are several algorithms to perform a hierarchical clustering, resulting in approximate dendrogram. This makes it possible to perform a clustering on big data sets. In this thesis the student will evaluate of several existing algorithms in terms of resource use and clustering quality. As part of this work, the student has to implement some of the algorithms to work on a GPU as they are not scalable enough for CPU computing. External resources:, mainly IV. SIDESTEP: MEASURING THE QUALITY OF A DENDROGRAM

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