Predict House price using advanced regression techniques. For better readability refer google colab link: https://drive.google.com/drive/folders/1bHMzi2ouXur6UJCwuOadFGXIBsa706OA?usp=sharing
A US-based housing company named Surprise Housing has decided to enter the Australian market. The company uses data analytics to purchase houses at a price below their actual values and flip them on at a higher price. For the same purpose, the company has collected a data set from the sale of houses in Australia. The data is provided in the CSV file below.
The company is looking at prospective properties to buy to enter the market. You are required to build a regression model using regularisation in order to predict the actual value of the prospective properties and decide whether to invest in them or not.
The company wants to know:
Which variables are significant in predicting the price of a house
How well those variables describe the price of a house.
You are required to model the price of houses with the available independent variables. This model will then be used by the management to understand how exactly the prices vary with the variables. They can accordingly manipulate the strategy of the firm and concentrate on areas that will yield high returns. Further, the model will be a good way for management to understand the pricing dynamics of a new market.
Below are some important metrics value for ridge and lasso regression :
Ridge
- Best alpha value: 0.8
- r2 score on train = 89.25
- r2 score on test = 87.53
- Root Mean Square Error Value on Test = 0.115644
Lasso
- Best alpha value: 0.0001
- r2 score on train = 89.36
- r2 score on test = 87.07
- Root Mean Square Error value on Test = 0.119989
- Python (pandas, numpy, matplotlib, Seaborn, sklearn, statsmodels etc)
I would like to acknowledge the UpGrad tutor and IIIT Bangalore for their collaboration in designing an advanced regression use case that effectively demonstrates house price prediction use cases, fostering practical understanding and application of regression techniques.
Created by [@subham0206] - feel free to contact me!