Introduction to stream: An Extensible Framework for Data Stream Clustering Research with R
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چکیده
منابع مشابه
Introduction to stream: An Extensible Framework for Data Stream Clustering Research with R
In recent years, data streams have become an increasingly important area of research for the computer science, database and statistics communities. Data streams are ordered and potentially unbounded sequences of data points created by a typically non-stationary data generating process. Common data mining tasks associated with data streams include clustering, classification and frequent pattern ...
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Clustering streams of continuously arriving data has become an important application of data mining in recent years and efficient algorithms have been proposed by several researchers. However, clustering alone neglects the fact that data in a data stream is not only characterized by the proximity of data points which is used by clustering, but also by a temporal component. The extensible Markov...
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In recent times there has been a surge of large scale information networks arising in various application domains, ranging from communication networks, cellphone call networks, social networks, email networks, road traffic networks, financial transaction networks, to name a few. In such applications there is a need to manage and process large data streams in near-real time. Examples of such que...
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ژورنال
عنوان ژورنال: Journal of Statistical Software
سال: 2017
ISSN: 1548-7660
DOI: 10.18637/jss.v076.i14