Enterprise AI Administration
Energy Cost Driver Model
Model Details · Telecom AI Model Registry
Model Details
Energy Cost Driver Model
Algorithm: XGBoostAPPROVED DESIGN
- Code
MDL-ENERGY-DRIVER- Version
- v0.1
- Owner
- Network Finance Analytics
- Governance owner
- AI Governance Board
Governance configuration shown for review and validation. Read-only.
Business purpose
Explain which site and operational drivers move energy and diesel cost
Production-recommended design specification. This record does not mean the model has been trained, fitted, deployed or validated.
Technical specification
- Model family
- Gradient Boosted Regression Trees
- Algorithm
- XGBoost
- Implementation library
- XGBRegressor
- Model type
- Regression
- Explainability method
- SHAP TreeExplainer
Implementation governance
- Governance status
- APPROVED DESIGN
- Implementation status
- MODEL DEVELOPMENT REQUIRED
- Validation status
- VALIDATION REQUIRED
- Lifecycle stage
- Design
- Current performance
- Not yet measured
- Refresh cadence
- Monthly
- Last reviewed
- —
- Next review due
- —
Business
- Mission area
- Cost Optimization
- Decision journey
- Cost & Capital Optimization
- Target variable
- energy_cost_per_site
- Output
- Driver contribution per site cluster
Input features
Governed variables, in feature-rank order
- 1.energy_cost_variance_pctEnergy cost versus budget for a site or region.
- 2.capacity_utilization_pctBusy-hour capacity utilisation of a site.
- 3.Outage countOutages per site in last 30 days
Related Intelligence
Linked governed records
KPIs (1)
Business rules (1)
Formulas (1)
Simulation models (1)