run glmfit , why get Warning: X is ill conditioned, or the model is overparameterized

run code for a linear regrssion. X has 5 predictors, Y is one response vector with ordinal values(1 to 5)

b = glmfit(X,Y);

Warning: X is ill conditioned, or the model is overparameterized, and some coefficients are not identifiable. You should use caution in making predictions.

similarly when running b = mnrfit(X, Y);

Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND = 4.607712e-20.

Does anyone know the reason, how to fix the issue?

[Ive J]

Can you share your data? Use paper clip icon to attach.

[Jie Li]

Thank you for looking at my problem. x, y data in the attached csv file.

[Jie Li]

data file

Answer 1

[Jeff Miller]

The problem is that the x1-x5 values sum to 24 in every row. This means that any one of the x's can be predicted from the rest of the x's, which is not allowed in regression models. I suggest you drop one of the x's from the predictor set.