From the course: Complete Guide to AI and Data Science for SQL Developers: From Beginner to Advanced
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Solution: Preprocessing - SQL Tutorial
From the course: Complete Guide to AI and Data Science for SQL Developers: From Beginner to Advanced
Solution: Preprocessing
(lively music) - [Instructor] Here's the solution to our challenge. First, multicollinearity occurs when independent variables in a regression model are highly correlated with each other. It's problematic because it can make it challenging to determine the individual impact of each variable on the target variable. This leads to less reliable predictions and potentially confusing insights. Secondly, the VIF or variance inflation factor. This is a tool used to detect multicollinearity. It quantifies how much the variance of an estimated regression coefficient is increased due to collinearity. A high VIF value indicates a high degree of multicollinearity. Thirdly, variables with VIF values exceeding five are considered problematic in terms of multicollinearity.
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