Project Title: AD 331 Predicting House Prices in Melbourne with Simple Linear Regression

By: Amde Wubshet

Dataset Used:

melb_data.csv

Target Variable

Price

Data Cleaning/Feature Engineering Summary

• For Data Cleaning: After reading the .csv, used the .dropna() method to remove missing values
• For Feature Engineering: Created a new numerical feature "HouseAge" that is created by taking the difference of the current year and the data from the "YearBuilt" column

Final Evalulation Metrics

• MSE = 395666478127.9991
• R2 = 0.09024356473991779