AGENT CLUSTERING DASHBOARD

PCA + K-Means · Performance Intelligence

Cluster Size Distribution

Number of agent-periods per cluster

Elbow + Silhouette Analysis

Optimal k selection metrics

Cluster Radar — Mean Metrics

Normalised mean feature values per cluster (0–1 scale)

PCA Scatter Plot — PC1 vs PC2

Each point is one agent-period. PC1 explains the most variance; PC2 the second-most.

Feature Distribution by Cluster

Box-like distribution per metric per cluster

Cluster Membership Over Time

Track how each agent's cluster assignment changes across periods

Agent Stability Rankings

Stability % = fraction of periods in modal cluster. Low values = frequent cluster switching.

Explained Variance per PC

Cumulative variance captured by each principal component

PCA Loadings Heatmap

Contribution of each original feature to each principal component

Documentation

Full documentation of the PCA + K-Means methodology, profiles, and drift analysis