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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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Impact Factor : 8.14
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| Paper Title: | House Price Prediction using Machine Learning |
| Authors Name: | Parth Tandon , Vijaya Choudhary , Abhay Pratap Singh |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_212255
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| Published Paper Id: | IJRTI2605007 |
| Published In: | Volume 11 Issue 5, May-2026 |
| DOI: | |
| Abstract: | The real estate market involves complex decision-making processes, including accurate house price estimation, financial planning, and loan approval analysis. Traditional methods of evaluating property prices and financial feasibility are often time-consuming and prone to errors. With the advancement of machine learning and data analysis, it is possible to develop intelligent systems that provide accurate predictions and financial insights. This paper presents a House Price Prediction using Machine Learning which supports systems that integrates multiple machine learning models (Classification ,Regression etc) and financial calculations into a single web application. The system uses regression techniques to predict house prices based on features such as area, number of rooms, city, and state. In addition, a classification model is implemented to predict loan eligibility based on financial parameters such as income, credit score, and employment status. The system also includes an EMI calculator and a rent-versus-buy analysis module, which helps users compare the long-term cost of renting and buying a property. These features enable users to make informed and data-driven decisions. The application is developed using Python, Flask, and Scikit-learn, providing a user-friendly interface for interaction. The proposed system demonstrates the practical application of machine learning in real estate and financial planning, offering a comprehensive solution for property price prediction and decision support. Buying a House is the most important decision in a person’s life therefore our model will help them with this. Additionally, our model also helps to find the best EMI and if Renting could be a better decision. |
| Keywords: | Machine Learning, House Price Prediction, Real Estate Analytics, Loan Eligibility Prediction, EMI Calculation, Rent vs Buy Analysis, Regression, Classification, Financial Decision Support System, Flask Web Application |
| Cite Article: | "House Price Prediction using Machine Learning", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 5, page no.a55-a59, May-2026, Available :http://www.ijrti.org/papers/IJRTI2605007.pdf |
| Downloads: | 000205562 |
| ISSN: |
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: IJRTI2605007
Registration ID:212255
Published In: Volume 11 Issue 5, May-2026
DOI (Digital Object Identifier):
Page No: a55-a59 Country: Greater Noida, Delhi NCR, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2605007 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2605007 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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