Read-only demo No credits charged No private job access
Clustering

Facility Profile Segmentation

Which facilities have similar operational profiles without using a target label?

An unsupervised workflow showing no-target readiness, cluster comparison, and segment-level review.

Demo outcome
HDBSCAN
Best model
Selected from replayed saved metrics.
0.420
Silhouette Score
Primary metric for this workflow.
21 seconds
Observed run time
Demo replay based on saved job behavior.
This workspace is a guided public replay.
Training, SHAP, report generation, prediction, job deletion, and billing actions are unavailable in demo mode.
Completed Demo ID: demo-clustering-segments
Saved-output workflow

The demo, handbook, and job page use the same saved outputs.

Each item below comes from the completed source job, so the public replay matches what users review after a real run.

Open AI Report tab
Data setup
Summary Only
The example records the data roles and checks shown in the replay.
None
Analysis checks
Summary Only
The replay explains the checks expected for this type of analysis.
None
Model explanation
Summary Only
The replay describes how model findings should be interpreted.
None
Reproducibility boundary
Available
The demo is read-only and does not run training, prediction, or billing.
None
Methods appendix
Available
A concise methods note is bundled with this public example.
methods_appendix.md
Dataset and roles

Readiness preview input

Rows
680
Features
10
Target
None
Format
Stata DTA
Status
Pass
features
Workflow steps

How the job moved

Confirm no-target workflow
Only feature columns are required for clustering.
Compare clustering families
Density, centroid, and hierarchical models were compared.
Review segment labels
Cluster summaries are descriptive and require analyst review.
Saved outputs

What users review

Cluster assignment table
outputs
Facility-level cluster labels for downstream review.
Cluster summary
report
Descriptive segment profile by feature group.
Model comparison
metrics
Silhouette and supporting unsupervised diagnostics.
Model comparison

Replayed performance table

Silhouette Score primary
Model Status Metric Value Training Time
HDBSCAN Best Silhouette Score 0.420 1.9s
KMeans Trained Silhouette Score 0.388 0.6s
Agglomerative Trained Silhouette Score 0.351 0.8s
DBSCAN Trained Silhouette Score 0.318 0.4s
Report summary

Decision-ready notes

  • This demo uses an unsupervised no-target workflow.
  • HDBSCAN produced the strongest separation among compared clustering methods.
  • Cluster labels are descriptive groupings and should be reviewed before action.
Cluster map
4 segments

Projected groups provide a visual starting point for analyst review.

Cluster profile
Distinct volume mix

Segment labels are descriptive and should be validated by domain experts.

No target label
Unsupervised

The workflow does not claim predictive accuracy against an outcome.

Live log replay

The event stream users see during a real run

Press Replay logs to stream the curated demo events.
Ready for your own data?

Use the real workflow with authentication and billing safeguards.

A real run requires sign-in, readiness preview, visible cost estimate, and confirmation before training starts.