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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: September 2025
Volume 10 | Issue 9
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 112
Article Submitted : 17662
Article Published : 7644
Total Authors : 20256
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| Paper Title: | House Price Prediction System using Machine Learning |
| Authors Name: | Sakshi Ashok Hole , Vishakha Bharat Biradar , Punam Motiram Dahikamble , Shrejal Satish Chopade , Dr. Khushbu R. Khandaid |
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IJRTI_204432
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| Published Paper Id: | IJRTI2506019 |
| Published In: | Volume 10 Issue 6, June-2025 |
| DOI: | |
| Abstract: | The project is to develop a machine learning-based system that accurately predicts the prices of residential properties by analyzing historical data and identifying patterns between various features and their market values. These features may include location, square footage, number of bedrooms and bathrooms, lot size, age of the property, and other relevant attributes. The project utilizes supervised learning algorithms such as Linear Regression, Decision Trees, Random Forests, and Gradient Boosting to train predictive models. It also involves key data preprocessing techniques like handling missing values, encoding categorical data, and feature scaling to enhance model performance. Evaluation metrics such as RMSE, MAE, and R² score are used to assess the accuracy of predictions. The goal is to offer reliable and transparent price estimations that assist buyers, sellers, investors, and real estate agents in making informed decisions. By automating the price prediction process, the system reduces manual errors, saves time, and brings consistency to property valuation. A user-friendly interface or dashboard may be included to enable easy interaction with the model, and the system is designed to be scalable for integration with real-time market data or new regions. Overall, this project showcases the potential of machine learning in transforming traditional real estate practices into smart, data-driven processes. |
| Keywords: | House Price Prediction System using Machine Learning |
| Cite Article: | "House Price Prediction System using Machine Learning ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 6, page no.a134-a145, June-2025, Available :http://www.ijrti.org/papers/IJRTI2506019.pdf |
| Downloads: | 000269 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2506019
Registration ID:204432
Published In: Volume 10 Issue 6, June-2025
DOI (Digital Object Identifier):
Page No: a134-a145 Country: Pune, Maharashtra , Maharashtra , India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2506019 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2506019 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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