Machine Learning Fundamentals › Linear Regression
What are common mistakes to avoid with Linear Regression
IntermediateAnswer
A common mistake is using linear regression on data with a clearly non linear relationship, which leads to poor predictions and misleading conclusions.
Real-world example A real estate company predicts house prices based on square footage, using linear regression to estimate how much price increases for each additional square foot.