How to evaluate clusters base on an attribute of the dataset? I have a data set of persons with attribute job that have 300 different nominal value.
attribute job have a lot of noise. I decide to cluster my data base on other attribute (other feature of person) that related to their job. I hope I reach to clusters with high correlation to job.

Now, I want to know, how much I were successful. In my opinion, more correlation between job and the clusters means more success. I found chi-squared as a method to check correlation between two nominal attributes. 
But the result is very low p-value for all clustering.

Is there any method to evaluate a clustering with a predefined class?
Use external cluster evaluation.

In particular, use ARI and NMI.