Robust Methods for Soft Clustering of Multidimensional Time Series †
Abstract
:1. Introduction
2. Robust Clustering Methods for Multivariate Time Series
3. Application to real data
4. Conclusions
Acknowledgments
References
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Company | ||||||
---|---|---|---|---|---|---|
AAPL | 0.083 | 0.146 | 0.299 | 0.365 | 0.066 | 0.041 |
MSFT | 0.107 | 0.049 | 0.213 | 0.356 | 0.099 | 0.176 |
AMZN | 0.865 | 0.017 | 0.051 | 0.032 | 0.010 | 0.025 |
GOOGL | 0.682 | 0.032 | 0.092 | 0.128 | 0.025 | 0.040 |
GOOG | 0.902 | 0.010 | 0.031 | 0.028 | 0.008 | 0.022 |
FB | 0.002 | 0.983 | 0.006 | 0.004 | 0.003 | 0.002 |
TSLA | 0.023 | 0.012 | 0.056 | 0.885 | 0.013 | 0.010 |
BRK.B | - | - | - | - | - | - |
V | 0.004 | 0.014 | 0.015 | 0.017 | 0.941 | 0.009 |
JNJ | 0.004 | 0.015 | 0.019 | 0.013 | 0.937 | 0.013 |
WMT | - | - | - | - | - | - |
JPM | 0.002 | 0.001 | 0.003 | 0.003 | 0.002 | 0.989 |
MA | 0.005 | 0.006 | 0.968 | 0.010 | 0.005 | 0.006 |
PG | 0.015 | 0.012 | 0.028 | 0.016 | 0.019 | 0.909 |
UNH | 0.006 | 0.924 | 0.026 | 0.013 | 0.022 | 0.008 |
DIS | 0.020 | 0.038 | 0.772 | 0.099 | 0.042 | 0.030 |
NVDA | 0.025 | 0.020 | 0.085 | 0.804 | 0.043 | 0.024 |
HD | - | - | - | - | - | - |
PYPL | 0.155 | 0.301 | 0.297 | 0.115 | 0.057 | 0.075 |
BAC | 0.076 | 0.086 | 0.225 | 0.067 | 0.060 | 0.485 |
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López-Oriona, Á.; D’Urso, P.; Vilar, J.A.; Lafuente-Rego, B. Robust Methods for Soft Clustering of Multidimensional Time Series. Eng. Proc. 2021, 7, 60. https://doi.org/10.3390/engproc2021007060
López-Oriona Á, D’Urso P, Vilar JA, Lafuente-Rego B. Robust Methods for Soft Clustering of Multidimensional Time Series. Engineering Proceedings. 2021; 7(1):60. https://doi.org/10.3390/engproc2021007060
Chicago/Turabian StyleLópez-Oriona, Ángel, Pierpaolo D’Urso, José A. Vilar, and Borja Lafuente-Rego. 2021. "Robust Methods for Soft Clustering of Multidimensional Time Series" Engineering Proceedings 7, no. 1: 60. https://doi.org/10.3390/engproc2021007060