August 2018
Intermediate to advanced
522 pages
12h 45m
English
Content preview from Machine Learning Algorithms - Second Edition
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Online Clustering
Sometimes, dataset X is too large, and the algorithms can become extremely slow, with a proportional need for memory. In these cases, it's preferable to employ a batch strategy that can learn while the data is streamed. As the number of parameters is generally very small, Online Clustering is quite fast and only a little bit less accurate than standard algorithms working with the whole dataset.
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