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2004 JMLR JMLR 2004

Weather Data Mining Using Independent Component Analysis

Abstract

In this article, we apply the independent component analysis technique for mining spatio-temporal data. The technique has been applied to mine for patterns in weather data using the North Atlantic Oscillation (NAO) as a specific example. We find that the strongest independent components match the observed synoptic weather patterns corresponding to the NAO. We also validate our results by matching the independent component activities with the NAO index. [abs] [ pdf ][ ps.gz ][ ps ]

🧭 Keyword Pioneer — spatio-temporal datum
🐝 Cross-Pollinator — Artificial Intelligence, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning
🌉 Interdisciplinary Bridge — Data Science & Analytics and Machine Learning
📈 Trend Setter — Data Mining

Authors

Jayanta Basak , Anant Sudarshan , Deepak Trivedi , M. S. Santhanam

Topics

Machine Learning > Core Methods > Representation Learning Machine Learning > Learning Types > Unsupervised Learning Data Science & Analytics > Methods > Data Mining

Keywords

independent component analysis spatio-temporal datum pattern mining weather data mining climate pattern pattern discovery
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