Title: Cluster analysis of dynamic data Author: Bc. Michal Marko Department: Department of Software and Computer Science Education Supervisor: RNDr. František Mráz, CSc. Supervisor's e-mail address: Frantisek.Mraz@mff.cuni.cz Abstract: The mail goal of this thesis is to choose or eventually to propose own modifications to some of the cluster analysis methods in order to observe the progress of dynamic data and its clusters. The chosen ones are applied to the real data. The dynamic data denotes series of information that is created periodically over the time describing the same characteristics of the given set of data objects. When applied to such data, the problem of classic clustering algorithm is the lack of coherence between the results of particular data set from the series which can be illustrated via application to our artificial data. We discuss the idea of proposed modifications and compare the progress of the methods based on them. In order to be able to use our modified methods on the real data, we examine their applicability to the multidimensional artificial data. Due to the complications caused by multidimensional space we develop our own validation criterion. Once the methods are approved for use in such space, we apply our modified methods on the real data, followed by the visualization and...
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:297879 |
| Date | January 2011 |
| Creators | Marko, Michal |
| Contributors | Mráz, František, Skopal, Tomáš |
| Source Sets | Czech ETDs |
| Language | Slovak |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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