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Evaluation of the Quality of Robust Clustering Algorithm TCLUST on the Example of Dataset of Air Pollutants Emission in Krakow
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Acquisition and data collection is currently a very dynamic processes. In order to obtain from data useful information, when huge quantities of data, the processing of the data is not a trivial task. Cluster analysis is very helpful in this and the result of grouping the result of grouping allows us to comprehend the available information and look at it from a different perspective. In any case, we are not able to show the entire spectrum of issues related to data analysis. Therefore we limit our discussion to the analysis of clusters, then we describe the TCLUST algorithm. The authors of the algorithm are H. Fritz, L. A. García-Escudero, A. Mayo-Iscar (see Fritz et al. 2011, 2012). In the paper we present the pros and cons robust clustering algorithm, and we discuss the available functions in the package tclust. Then on the example of dataset of air pollutants emission in Krakow we try to evaluate the quality of robust clustering algorithm.
Title: Evaluation of the Quality of Robust Clustering Algorithm TCLUST on the Example of Dataset of Air Pollutants Emission in Krakow
Description:
Acquisition and data collection is currently a very dynamic processes.
In order to obtain from data useful information, when huge quantities of data, the processing of the data is not a trivial task.
Cluster analysis is very helpful in this and the result of grouping the result of grouping allows us to comprehend the available information and look at it from a different perspective.
In any case, we are not able to show the entire spectrum of issues related to data analysis.
Therefore we limit our discussion to the analysis of clusters, then we describe the TCLUST algorithm.
The authors of the algorithm are H.
Fritz, L.
A.
García-Escudero, A.
Mayo-Iscar (see Fritz et al.
2011, 2012).
In the paper we present the pros and cons robust clustering algorithm, and we discuss the available functions in the package tclust.
Then on the example of dataset of air pollutants emission in Krakow we try to evaluate the quality of robust clustering algorithm.
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