turn on suggestions

Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.

Showing results for

Find a Community

- Home
- /
- Analytics
- /
- Data Mining
- /
- Subset Decision Trees Within Enterprise Miner

Topic Options

- Subscribe to RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Highlight
- Email to a Friend
- Report Inappropriate Content

08-26-2015 04:39 PM

I think I need the Code Node to accomplish this, but I am not sure.

I am running a Decision Tree on a set of data composed of about 10,000 records. The dependent variable is nominal/dichotomous, and I expect about 90% of the data will be predicted to be a 0 while the other 10% will be predicted to be a 1.

I then want to put another Decision Tree into the project. That one will use a different continuous dependent variable and it will be only for cases that are predicted to be 0 for the first Decision Tree- again, around 9,000 cases.

It sounds kind of basic, but kind of not. Either way, can anyone suggest the best way to do things in Enterprise Miner for this? Thank you. Much appreciated.

FOLLOW-UP:

Actually the TwoStage Node seems like it will suit my needs well. However, I am modeling two differeent dependent/response variables. One for categorical, and one continuous. So perhaps that is not usable.

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Highlight
- Email to a Friend
- Report Inappropriate Content

08-27-2015 09:19 AM

I think TwoStage will do exactly what you want. Just set both dependent variables as Targets in your Input Data node, and in the TwoStage node, change the Filter property to Non-Events, and Value Model to Tree. You just need to be sure you are using the correct Order (Ascending) for the nominal target so that 0's are treated as the event, then the predicted non-0s will be excluded from the second tree where you are modeling the continuous target.