Introduction Ordinary Least Squares is a method which helps us estimate the unknown parameters in the Linear regression model. How does it estimate the parameters though? Well, it estimates the parameters by minimizing the sum of squared residuals. The way it does is , it draws a line through the data points such that the squared…Read more
Multicollinearity
Multicollinearity using VIF
Introduction Collinearity is a condition in the data where we have 2 features which are heavily correlated with each other. In such situations, we could check the Collinearity using a heat map and then omit one of the features based on the results. Multicollinearity on the other hand is a more complicated problem to solve. In Multicollinearity, chances…Read more