What is clustering in data visualization?

What is clustering in data visualization?

Clustering in data visualization is a technique used to group similar data points together, making patterns easier to identify.

How does clustering help in analyzing data?

Clustering helps by revealing natural groupings in data, which can highlight trends and insights that may not be obvious.

What are some common clustering algorithms?

Some common clustering algorithms include K-means, hierarchical clustering, and DBSCAN.

Can you explain K-means clustering?

K-means clustering partitions data into K distinct clusters based on feature similarity, minimizing variance within each cluster.

What are the limitations of clustering?

Limitations include sensitivity to outliers, the need to specify the number of clusters, and potential difficulty in interpreting results.