House Market Prediction Using Machine Learning
This study compares tree-based machine learning algorithms for predicting Bucharest residential apartment prices. Using a dataset from March 2025, comprehensive preprocessing—including imputation, categorical encoding, and feature engineering (e.g., distance to public transport)—was applied. Models...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Bucharest University of Economic Studies
2025-01-01
|
| Series: | Database Systems Journal |
| Subjects: | |
| Online Access: | https://www.dbjournal.ro/archive/36/36_6.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | This study compares tree-based machine learning algorithms for predicting Bucharest residential apartment prices. Using a dataset from March 2025, comprehensive preprocessing—including imputation, categorical encoding, and feature engineering (e.g., distance to public transport)—was applied. Models were optimized via grid search with 5-fold cross-validation and evaluated using RMSE, MAE, and R². Results show XGBoost outperforms Random Forest and Decision Tree models across all metrics. |
|---|---|
| ISSN: | 2069-3230 |