About WendyCzika

WendyCzika · ‎04-22-2018

Please see this SAS note for info: http://support.sas.com/kb/43/711.html

WendyCzika · ‎04-19-2018

The HP Cluster nodes aren't fitting a model, just assigning observations to clusters. You could try using one of the modeling nodes after each of the clustering nodes and then do Model Comparison on those.

WendyCzika · ‎04-18-2018

You should be able to use the Group Processing nodes (Start Groups and End Groups) to do this: set up the flow: Input Data > Start Groups > Cluster > End Groups, and in the Start Groups node, open the Variables editor and set the Grouping Role for Sector to Stratification. You might need to set the Level of Sector to Nominal first in the Input Data node.

WendyCzika · ‎04-17-2018

You can create a Model Package of your flow by right-clicking on the Model Comparison node at the end - this will essentially create a zip file that can be used to re-create your flow, then you can delete your diagram and you can re-create your diagram from the Model Package if you ever need to (though you would need to re-run it to get your results back).

WendyCzika · ‎04-10-2018

Are you creating a Test partition with the Data Partition node? If not, then you can do this: make sure the role of the Input Data node for your out-of-time data is set to Test (assuming you have the target in that data), then connect that directly to the HP Forest node. You don't need the Score node and second Model Comparison node; when you re-run the first MC node, it should now include assessment on this test or hold-out data. If you are creating a Test partition with the Data Partition node, there still might be a way to do it that I'm not thinking of yet...

WendyCzika · ‎04-09-2018

You can use Gini impurity as the splitting criterion when growing the decision tree, which has formula:

WendyCzika · ‎04-09-2018

Have you taken a look at the Incremental Response node?

WendyCzika · ‎03-26-2018

If you click on the ellipsis next to the Exported Data property for a node, then click the Explore... button, there you will see the Actions menu with the Plot option, then Box on the left. You can also create a Box plot for any tables that show up in the Results of a node by selecting the table, then View > Plot... .

WendyCzika · ‎03-23-2018

To get KS or any ROC-related measure, you will need to use a Model Comparison node after your Regression node. I'm not sure why those charts would be coming up blank though. Are you getting effects included in your model?

WendyCzika · ‎03-13-2018

I'd suggest contacting SAS Technical Support for this issue: https://support.sas.com/en/technical-support.html

WendyCzika · ‎03-13-2018

I'd suggest contacting SAS Technical Support for this issue: https://support.sas.com/en/technical-support.html

WendyCzika · ‎03-08-2018

Maybe one of these posts will help? https://communities.sas.com/t5/SAS-Communities-Library/Time-Series-Exploration-by-Example-in-SAS-Enterprise-Miner/ta-p/233091 https://communities.sas.com/t5/SAS-Communities-Library/Tip-Your-First-Time-Series-Forecasts-with-SAS-Enterprise-Miner/ta-p/223537

WendyCzika · ‎03-06-2018

Yes, you can definitely give it a try - you might want to do Variable Selection first, then you can try either the Neural Network node or HP Neural from the HPDM tab to take advantage of parallel processing.

WendyCzika · ‎03-02-2018

The SAS Enterprise Miner Reference Help (try this link: http://go.documentation.sas.com/?docsetId=emref&docsetTarget=p0zbgj1tu3h1uhn1x6regixbdg7v.htm&docsetVersion=14.3&locale=en) has a lot of information including a section on Preparing the Data and many other details about how neural networks work. If the link above doesn't work, start here: http://support.sas.com/documentation/onlinedoc/miner/index.html#minercurrent Click on SAS Enterprise Miner 14.3: Reference Help Then look under Node Reference: Model Nodes > Neural Network Node : Reference

WendyCzika · ‎03-01-2018

In the Properties panel of the Cluster node, you can click on the ellipsis next to Exported Data to bring up a window that allows you to view your data to see what observation is in which cluster.

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