Subscribe Bookmark RSS Feed

Variable Selection for Decision Trees (Uplift Modelling)

Laurents_Mohr

Occasional Contributor

Joined:

Apr 12, 2017

Hi all,

 

I would like to know what method JMP is using for the variable selection in decision trees.

I could not find an answer to this question. I read in a paper by Radcliffe and Surry that Low Qini Estimates (LQE's) are their suggestion for it.

 

I am fairly new to JMP and definetly not a statistic expert.

I am currently writing my Bachelor thesis with a partner company, where I am supposed to measure the uplift of their marketing campaigns. I have to accumulate 40 pages on this, so just the results won't do it, I need to know say what and why things happen.

 

If anyone has experience with uplift modelling of marketing campaigns, but can't answer the question above, still let me know. Your experience could be of great help to me!

 

Thank you in advance and kind regards,

Laurents 

 

1 ACCEPTED SOLUTION

Accepted Solutions
txnelson

Super User

Joined:

Jun 22, 2012

Solution

There is a whole section on the statistical details on decision trees in the JMP book, "Predictive and Specialized Modeling".  It is available in JMP

     Help==>Books==>Predictive and Specialized Modeling

Jim
2 REPLIES
txnelson

Super User

Joined:

Jun 22, 2012

Solution

There is a whole section on the statistical details on decision trees in the JMP book, "Predictive and Specialized Modeling".  It is available in JMP

     Help==>Books==>Predictive and Specialized Modeling

Jim
Laurents_Mohr

Occasional Contributor

Joined:

Apr 12, 2017

lol this is great! Thank you!

 

I looked on the web, but not within the software!