Automating Regression Models :KXEN

Note : I have used KXEN both for modeling internet leads in 2008 as well as for consumer finance propensity models in 2006.These  are my personal views.

An extremely useful software and to my surprise very much under used in Industry is KXEN. It can be used for building regression models, time series models as well clustering models as well. I have used it primarily for regression models and clustering though. What KXEN does is it uses all the rules that modelers make for adding, dropping , and manipulating variables and automates them . It then produces the exported model code into PMML, SAS, SPSS and even SQL code for direct model execution. The validity of the model is tested by the modeler using a nice variety of graphs.The software uses a properietary algorithm called SRM.

The latest version is version 5 and it is available here http://www.kxen.com/index.php?option=com_content&task=view&id=61&Itemid=166

 

 

It is one of the best automated modelings I have used and been trained in, so if you are interested you can try an evaluation version here. The support team is excellent , and so are the sales chap ( they neither oversell nor undermine the competition) .It can cut down on both modeling time as well training time for learning the model. If combined with WPS or R to clean data in the initial stage it is good solution for renting or buying especially for cost savvy businesses.

  The only caveat if at all is it needs data to be cleaned  for formatting and variable type issues before entering for modeling, but that can be easily done.

Author: Ajay Ohri

http://about.me/ajayohri

One thought on “Automating Regression Models :KXEN”

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s