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03-10-2017 12:27 PM

I am new to SAS enterprise miner and I have only been using the Model tab for model building such as Cluster,Decicion tree and Regression.

I have seen the HPDM Tab and it contains HP CLuster,HP Regression etc

My question is;what is the diference between cluster node and HPCluster node,or difference between Regression node and HP REGRESSION.

I'm a data mining novice self learning,detail and easy to understand explanation is much welcome..

Thanks

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03-13-2017
05:26 AM

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03-10-2017 01:12 PM

SAS Enterprise Miner High Performance (HP) data mining nodes have been specially developed to take advantage of parallel processing in both multithreaded single-machine mode and distributed multiple-machine mode. This is useful with large data sets and data stores. Note that these nodes aren't necessarily a full replacement for their non-HP counterparts, and that there are some nodes that only exist in HPDM, for example: HP Bayesian Network Classifier, HP Forest, and HP GLM. Here is information about the individual procedures:

And see the Enterprise Miner Reference Help for more informationa about the individual HPDM nodes.

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03-13-2017
05:26 AM

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03-10-2017 01:12 PM

SAS Enterprise Miner High Performance (HP) data mining nodes have been specially developed to take advantage of parallel processing in both multithreaded single-machine mode and distributed multiple-machine mode. This is useful with large data sets and data stores. Note that these nodes aren't necessarily a full replacement for their non-HP counterparts, and that there are some nodes that only exist in HPDM, for example: HP Bayesian Network Classifier, HP Forest, and HP GLM. Here is information about the individual procedures:

And see the Enterprise Miner Reference Help for more informationa about the individual HPDM nodes.

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03-10-2017 02:06 PM

Also - be sure to check out Radhikha Myneni's excellent overview of HPDM in a series of tips starting with https://communities.sas.com/t5/SAS-Communities-Library/SAS-High-Performance-Analytics-tip-1-How-it-d...