Analysis of Real Estate Prices in Texas
George Kurian (Florida A&M University)
The project will involve study of the real estate market in Texas, finding any patterns from just the volume and the prices for residential homes and not commercial properties, then look at the relationships between the price trend and volume of sales trend to the employment data, interest rates, GDP, inflation rate. Data for the first 5 years will be used and a model will be developed using Decision Trees and Neural network, and also clustering method will be used in order to identify, the trends in different counties as the data for each county in Texas is also available. Once a model based on the relationships is identified it will be tested in predicting the prices and the amount of sales over the next year and the results using both the methods will be compared. Based on the errors between the actual values and the predicted values modifications can be made to the models, which will be later used to predict prices for the next year, and the process will be continued till we have a robust model. These analysis will also be implemented using R and those results will also will also be compared to improve the model.