An Innovative Method for Housing Price Prediction using Least Square - SVM
- Title
- An Innovative Method for Housing Price Prediction using Least Square - SVM
- Creator
- Goel Y.K.; Swaminathen A.N.; Yadav R.; Kanthamma B.; Kant R.; Chauhan A.
- Description
- The House Price Prediction is often employed to forecast housing market shifts. Individual house prices cannot be predicted using HPI alone due to the substantial correlation between housing price and other characteristics like location, area, and population. While several articles have used conventional machine learning methods to predict housing prices, these methods tend to focus on the market as a whole rather than on the performance of individual models. In addition, good data pretreatment methods are intended to be established to boost the precision of machine learning algorithms. The data is normalized and put to use. Features are selected using the correlation coefficient, and LSSVM is employed for model training. The proposed approach outperforms other models such as CNN and SVM. 2023 IEEE.
- Source
- 2023 4th International Conference on Electronics and Sustainable Communication Systems, ICESC 2023 - Proceedings, pp. 928-933.
- Date
- 2023-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- House Price Prediction (HPP); Least Square Support Vector Machine (LSSVM); Normalization
- Coverage
- Goel Y.K., Surajmal University, Computer Science Engineering, Uttarakhand,(Udham Singh Nagar), Kichha, India; Swaminathen A.N., Adi Shankara Institute of Engineering and Technology, Civil Department, Kerala, kalad, India; Yadav R., Graphic Era Hill University, Department of Computer Science and Engineering, Dehradun, India; Kanthamma B., Gitam Deemed to Be University, Electrical, Electronics and Communications Engineering (EECE), Andhra Pradesh, Visakhapatnam, India; Kant R., Shoolini University, Cse Department, Himachal Pradesh, Solan, India; Chauhan A., Christ (Deemed to Be University), Department of Life Sciences, Karnataka, Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835030009-3
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Goel Y.K.; Swaminathen A.N.; Yadav R.; Kanthamma B.; Kant R.; Chauhan A., “An Innovative Method for Housing Price Prediction using Least Square - SVM,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 26, 2025, https://archives.christuniversity.in/items/show/19886.