Q:

Chi-squared Vs Mutual information

Is chi-squared feature selection better than Mutual information based feature selection mechanism?

A:

They are related, so I don't suspect there to be a big difference (hence, go for mutual information if it's easier to calculate).
I haven't seen a formal argument for this, but my logic is:

A g-test is a derivate of mutual information ($G=2\cdot N \cdot MI(r,c)$, cfr. wiki link)
A Chi-squared leads
to the same conclusion as a g-test for reasonably sized samples

Therefore, Chi-squared and MI lead to more or less the same results for reasonably sized samples. In other cases, it will deterministically depend on the dataset properties.

