June 2020
Intermediate to advanced
382 pages
11h 39m
English
Content preview from 40 Algorithms Every Programmer Should Know
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Limitation of k-means clustering
The k-means algorithm is designed to be a simple and fast algorithm. Because of the intentional simplicity in its design, it comes with the following limitations:
The biggest limitation of k-means clustering is that the initial number of clusters has to be predetermined.
The initial assignment of cluster centers is random. This means that each time the algorithm is run, it may give slightly different clusters.
Each data point is assigned to only one cluster.
k-means clustering is sensitive to outliers.