Nada-elkamel/Aqari-Tunisia-Property-Estimator
Domaine:
socioeconomicType de record:
software
Créateur:
Nad
HĂ´te:
# 🏠Aqari-Tunisia-Property-Estimator
🔍 Overview
Aqari is a machine learning pipeline designed to predict real estate prices in Tunisia. Built with a philosophy of "Zero rows dropped", the system handles missing values through advanced imputation techniques and manages outliers via Winsorization rather than deletion.
Key Objectives
âś… Preserve all 8,129 property listings without dropping rows
âś… Handle missing values using multivariate imputation strategies
âś… Engineer meaningful features from raw data
âś… Train and compare multiple regression models
âś… Deploy an interactive web application for instant price estimation
đź“Š Dataset
| **Property** | **Value** |
| ------------------- | ----------------------------------- |
| Source | dataSetFull.csv |
| Total Rows | 8,129 listings |
| Original Features | 26 columns |
| Target Variable | price_tnd (Price in Tunisian Dinar) |
| Geographic Coverage | 24 Governorates across Tunisia |
Feature Categories
đź“Ť Location Features
├── governorate, city, location
├── latt, long, distance_to_capital
🏗️ Structural Features
├── Area, pieces, room, bathroom
├── age, state, garage
✨ Amenities (Binary Flags)
├── garden, concierge, beach_view, mountain_view
├── pool, elevator, furnished, equipped_kitchen
├── central_heating, air_conditioning
đź’° Target
└── price_tnd, price_eur
Missing Value Summary (Before Imputation)
| **Feature** | **Missing Count** | **% Missing** | **Imputation Strategy** |
| ------------------ | ----------------- | ------------- | -------------------------------- |
| age | 4,145 | 50.99% | Median imputation |
| price_tnd | 1,708 | 21.01% | IterativeImputer (BayesianRidge) |
| city | 1,316 | 16.19% | Mode per governorate |
| pieces …