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Comparison of Distance Measurement in Time Series Clustering for Predicting Bitcoin Prices | IEEE Conference Publication | IEEE Xplore

Comparison of Distance Measurement in Time Series Clustering for Predicting Bitcoin Prices


Abstract:

Since the development of Bitcoin, the first blockchain-based cryptocurrency, many cryptocurrencies have formed and have traded in markets. The integrity and anonymity of ...Show More

Abstract:

Since the development of Bitcoin, the first blockchain-based cryptocurrency, many cryptocurrencies have formed and have traded in markets. The integrity and anonymity of cryptocurrency was enough to raise its value and its price gained worldwide attention. Therefore, many studies are being carried out to predict the price of cryptocurrency for make a profit. We cluster time series through K-Medoids algorithm and train and evaluate each cluster with predictive models. We also examine the predictive performance in Bitcoin price according to the various distance measurement of clustering.
Date of Conference: 22-25 September 2020
Date Added to IEEE Xplore: 23 October 2020
ISBN Information:
Print on Demand(PoD) ISSN: 2576-8565
Conference Location: Daegu, Korea (South)

Funding Agency:


References

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