Clustering using OPTICS by MAQ Software analyzes and identifies data clusters. The algorithm relies on density-based clustering, allowing users to identify outlier points and closely-knit groups within larger groups. This visual includes adjustable clustering parameters to control hierarchy depth and cluster sizes. R package dependencies (auto-installed): Dbscan, plotly, ggplot2.

Key features:

• Data is scaled and pre-processed automatically, eliminating the need to do so externally.

• Hover tooltips and zoom effects.

• Capability to manually adjust the parameters of the clustering model.

For any feature requests or questions about this visual, please send an e-mail to our team at support@maqsoftware.com.