I understand that imbalance or skew in the target variable within your training data can negatively impact effectiveness. Does the same apply to the predictor/independent variables?
y ~ B0 + B1*x1 + B2*x2
Consider this simple example. I am trying to predict
y, a categorical variable, from two variables
x2 which are also categorical variables. If I have an imbalanced set of
y values, this could be a bad thing. What if I have an imbalanced set of
x2? Could the same issue apply?