November 2017
Beginner to intermediate
366 pages
7h 59m
English
Content preview from R Data Analysis Projects
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Introducing stream clustering
Clustering can be defined as the task of separating a set of observations/tuples into groups/clusters so that the intra-cluster records are similar and the inter-cluster records are dissimilar. There are several approaches to clustering when we are dealing with data at rest. In streaming data, data continues to arrive at a particular rate. We don't have the luxury of accessing the data randomly or making multiple passes on the data. Among the data stream clustering methods, a large number of algorithms use a two-phase scheme which consists of an online component that processes data stream points and produces summary statistics, and an offline component that uses the summary data to generate the clusters.
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