Overview
Key metrics from 10,000 properties across 5 metro micro-markets
Total Properties
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Synthetic Dataset
Features
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Before PCA
Mean Valuation
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₹
Best Model R²
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Valuations by Micro-Market
Average ₹Valuations by Sector
Average ₹Market Distribution
CountSector Distribution
CountPCA Dimensionality Reduction
Principal Component Analysis reducing feature space while preserving 95%+ variance
Original Features
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PCA Components
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Variance Retained
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Reduction
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Explained Variance Ratio per Component
CumulativePCA Component Feature Importances (Random Forest)
RelativeEnsemble Model Performance
Comparison of Random Forest, Gradient Boosting, AdaBoost, and Stacking Ensemble
R² Score Comparison
Higher is BetterRMSE Comparison (₹)
Lower is BetterActual vs Predicted Valuations
Stacking Ensemble| Model | R² Score | RMSE (₹) | MAE (₹) |
|---|
Property Valuation Predictor
Enter property features to get an AI-powered valuation estimate
Property Features
Latitude
Longitude
💡 Tip: Click on the Micro-Market Map to select coordinates directly!
3
80
0.70
20
3
0.70
Configure property features and click
"Estimate Valuation" to see the prediction
Micro-Market Spatial Map
Interactive visualization of property locations across 5 metro micro-markets