Learning from kernels, following and understanding their code.
Building my own model and use the result as my Graduate Thesis in Shenzhen university.
https://www.kaggle.com/c/zillow-prize-1
Housing price has great influence in the development of economic and is also important to the stability of our society. Thus the study of housing price is always hot in our society. Building a housing price prediction model is always a effective way to study about housing price. In the past, people can only access limited data due to the era. Nowadays, the data that people can access is much larger and more complex.
Machine learning algorithm has been proved to be a effective ways to deal with big data in many different area. This article is focus on improve the accuracy of housing price prediction model by using machine learning algorithm. By using the data from Truman State University,this article compare the accuracy of machine learning model and traditional multiple linear regression model.
The study result shows that compared to the traditional multiple linear regression model the machine learning model has a great improvement in the accuracy.