What is the k-means algorithm?
An example of an AI chatbot conversation about the k-means clustering algorithm.
What is the k-means algorithm?
The k-means algorithm is a popular clustering method used to partition data into k distinct groups based on feature similarity.
How does the k-means algorithm work?
It works by initializing k centroids, assigning data points to the nearest centroid, and then updating the centroids based on the assigned points.
What are some applications of k-means clustering?
K-means is used in market segmentation, image compression, and organizing computing clusters, among other applications.
What are the limitations of the k-means algorithm?
Some limitations include sensitivity to initial centroid placement, difficulty with non-spherical clusters, and the need to specify k in advance.
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