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Machine Learning Resources

multicollinearity

Why does multicollinearity result in poor estimates of coefficients in linear regression?

In matrix form, the vector of coefficient estimates is derived using the formula: (X’X)-1X’Y, where X is the design matrix where the rows correspond to the observations and columns to the features, and Y is the vector of target values.

Doesn’t polynomial regression violate the multicollinearity assumption for Linear Regression?

While the original variable will likely be correlated with a higher order term constructed from the same variable, multicollinearity is not an overt cause of concern

What is multicollinearity and how can that be identified?

Multicollinearity occurs when one or more predictors experience high correlation between each other.