Rajil Ramakrishnan Thykkandy

Developed a business process re-engineering model on small and medium sized enterprise in real estate sector using Machine Learning techniques to predict the price of the property in the future. This technique will help the SMEs to compete in the market with the existing big firms and to create an adequate profit through sales in the future.

Models used in Machine Learning are:

• Linear Regression
• Decision Tree
• Random Forest

The data set of Melbourne City in Australia has been taken for the research. The prices of the property is determined by the number of the rooms, accessibility, land mark and date build.

Out of the three techniques the Random Forest technique gives the highest positive prediction score compared to rest of the two techniques. The price prediction is done by creating two data sets X and Y which are training set and validation set on the basis of price and a random number generator was used to decide how to divide the price. Both test_x predictions and test_y predictions are compared to see which has a better accuracy score.