Clustering of Financial Account Time Series Using Self Organizing Maps
This thesis aims to cluster financial account time series by extracting global features from the time series and by using two different dimensionality reduction methods, Kohonen Self Organizing Maps and principal component analysis, to cluster the set of the time series by using K-means. The results...
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| Format: | Others |
| Language: | English |
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KTH, Matematisk statistik
2021
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-291612 |