Going through the paper of BFTree(Best First Decision Tree) from (Haijian Shi (2007). Best-first decision tree learning. Hamilton, NZ). I read for pre-pruning do a local attribute selection. And the goal is to find whether the attribute is significantly correlated with the class.(stop further splitting if no attributes are significantly correlated with the class otherwise do the splitting). For that matter chi-squared test is used as the Statistical significant test.
Can some one please help to understand how the test is performed.
I see the formula to be used to get the chi squared statistics is
but how its used here as to find any correlation between the attribute and the class.