Hi, I've been working with a big and sparse matrix (over 5,000 columns -dummy variables- and 2M observations). For every observation, only 20-30 columns of the 5,000 contain a value. All of the 5,000 columns are independent variables, except for one, which is the dependent I need to explain. Running proc Logistic on that matrix, besides that technically results in an 'out of memory', is not a solutions as I would have to run it on a regularly basis. Using IML, with sparse, dense and full functions I can get rid of the zeroes and store only the significant values. Hence, my question arises as to how can I run proc logistic / glimmix on that resulting matrix, as it is totally distorted from the original one. And further, how could I be able to extract insights from the results of these procedures relating to the original matrix an its variables. Thank you for your time. Kind Regards, Alexis.
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