Write A Code Using Linear Regression and Neural Layered Structure To Predict The House Price

DOI

10.2991/978-94-6463-370-2_70How to use a DOI?

Keywords

Linear Regression; neural layered structure; predict the house price

Abstract

House price prediction is a challenging task, and for home buyers, it is difficult to accurately predict house prices due to the complexity and dynamics of the real estate market. Secondly, as far as the data is concerned, house price prediction is affected by several indicators and it has a great deal of randomness, so this is not easy for a machine to predict. The essence of house price prediction is to analyze and process the text, i.e. to do regression tasks. Therefore, in this essay, we propose a method for house price prediction by using linear regression and a neural layered structure. We demonstrate the effectiveness of these techniques on a dataset of 506 records from house price reports in Boston, Massachusetts, USA. Linear regression models provide an initial understanding of data trends, while neural network models use the power of deep learning to capture more complex patterns and relationships. Linear regression is a supervised learning algorithm used for predicting a continuous output based on input features. It assumes a linear relationship between input variables and the target variable. It’s a suitable choice when you have a dataset with numerical features and a continuous target variable. The neural network refers to the human brain neuron network and forms different networks according to different connection methods to complete information processing and establish a certain model.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Kehan Chen
AU  - Wanting Lu
AU  - Yicheng Yan
PY  - 2024
DA  - 2024/02/14
TI  - Write A Code Using Linear Regression and Neural Layered Structure To Predict The House Price
BT  - Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
PB  - Atlantis Press
SP  - 695
EP  - 704
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-370-2_70
DO  - 10.2991/978-94-6463-370-2_70
ID  - Chen2024
ER  -