Multicollinearity: Multicollinearity is a problem when there is very high correlation between predictors. It increases the noise in the datawhich result to inaccurate results. Reasons: 1. It might happened because of wrong dummy variables. 2. It might possible that one predictors get calculated with other variables and we included both the variables in the
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