Hi there, I'm using SAS Enterprise Miner to perform clustering of customers on specific dataset at one extraction date. After finalize the model, I wanted to score a new dataset to existing clustering model (k-means in SAS-EM). I found out that there are 80% of record classified as no cluster assigned. Only few of them there were be able to scored with segment number attached. I supposed it is from the data transformation part that I did binning continuous data to nominal data within SAS-EM. But I have reviewed all of the variables of the model and all the ranges were covered and there is no missing value in any cell of the table used to model and score. So, I wondered if it is the algorithm limit that they treat 80% of scoring data as outlier that SAS-EM cannot assigned any segment to specific cluster from the training model? Is there any point that I can force the scoring cutoff point to assign all the scoring record data to the nearest possible cluster? Thus, all the scoring record can have a segment label assigned. Thanks,
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