Algorithms · Level 2 of 5
K-Means
A clustering method alternating assignments and centroid updates to reduce within-cluster squared distances.
Its solutions depend on initialization and the chosen number of clusters.
Example
Points are partitioned around five learned centers.
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K-Means. A clustering method alternating assignments and centroid updates to reduce within-cluster squared distances. Its solutions depend on initialization and the chosen number of clusters. For example: Points are partitioned around five learned centers.
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