Dealing with collinearity
I am having difficulties with my data. I have 96 attributes and I need to complete a scientifically robust method for checking collinearity between the attributes. I have been fiddling with the 'remove correlated attributes' operator.
I have a few questions pertaining to this:
a) In the situation where you have 3 attributes and 2 are highly correlated to the third what is the criteria in which this operator selects an attribute?
b) I want to remove attributes which have a correlation equal to or greater than 0.75. But, this needs to apply to both positive and negative correlations meaning if a correlation is equal to -0.83 I need this to be removed also. How can I get this operator to apply these requirements?
If there are any suggestions of better methods that Rapidminer is capable of for dealing with collinearity I would also appreciate any further suggestions.