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Outlier Detection for Temporal Data (Synthesis Lectures on Data Mining and Knowledge Discovery)

Manish Gupta, Jing Gao, Charu Aggarwal, Jiawei Han




[PDF.ox36] Outlier Detection for Temporal Data (Synthesis Lectures on Data Mining and Knowledge Discovery)

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 | #2962768 in Books |  2014-04-01 | Original language:English | PDF # 1 |  9.25 x.30 x7.50l,.52 | File type: PDF | 130 pages

||0 of 2 people found the following review helpful.| Not worth its price|By Customer|Really hard book to read even for someone with a Phd.|About the Author|Microsoft India and International Institute of Information Technology, Hyderabad, India

Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc. Initial research in outlier detection focused on time series-based outliers (in statistics). Since then, outlier detection has been studied on a large variety of data types including high-dimensional data, uncertain data, str...

You easily download any file type for your device.Outlier Detection for Temporal Data (Synthesis Lectures on Data Mining and Knowledge Discovery)   |  Manish Gupta, Jing Gao, Charu Aggarwal, Jiawei Han. I was recommended this book by a dear friend of mine.

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