Cluster Analysis Visualization - Data Grouping and Outlier Detection #85039 (License: Personal Use)

This diagram illustrates unsupervised clustering-likely k-means or DBSCAN-where most data points form dense groups inside a flexible purple boundary. Two outliers lie outside: a blue point near the y-axis and a red point near the x-axis, indicating anomalies or edge cases. The clean vector-style rendering supports use in academic, technical, or data science presentations.

Used in machine learning tutorials, statistics courses, or AI documentation to explain clustering algorithms, classification boundaries, and outlier detection. Matches user intent for visual learners seeking conceptual clarity on data grouping.