Comments on: Rapidminer 5.0 Video Tutorial #6 – Creating a Decision Tree with Rapidminer 5.0

By: Tom

Tom — Tue, 26 Apr 2011 22:18:21 +0000

Hi Cort! If you want to know the correlation between your variables, you could use RM’s correlation matrix operator. The Decision Tree operator can’t handle a numerical label (output) so you’d have to transform it into some sort of nominal label if possible. You can try using the discretizing operators to transform your numerical label into a nomimal one. Good luck and thanks for watching the tutorials!

By: Cort

Cort — Tue, 26 Apr 2011 21:20:00 +0000

Hey Thomas, I loved your tutorials…keep up the rockin’ work. I must say though that you make it look very easy. I Have been having extreme difficulty creating a decision tree using the following fields in an Excel file: bought price,lender,state,employment,pay period,monthly income,requested amt,employed months.
I want to make the Label column ‘bought price’ but then it complains about not being able to do a split test with numerical. Perhaps I’m going about this model the wrong way? Basically I want to find the relationships/correlations as it pertains to ‘bought price’ and the other variables. Any help would be sincerely appreciated.

By: Tom

Tom — Sun, 19 Sep 2010 09:23:43 +0000

Hi Kihmo,
I’m working on book with the Rapid-i team that addresses this very issue. We hope to have it ready for press in April 2011.

By: Kihmo

Kihmo — Thu, 16 Sep 2010 20:31:42 +0000

Hi Tom,

thank you so much for these great tutorials! It’s really a professional level where it is fun for the visitors to learn more!

If you plan to make more tutorials in future I would kindly ask for a session on the different types of operators in Rapid Miner. Something like a rough overview without having to read tons of documentation… For what types do I use a neural net? What are typical question where I use a cross validation to find an answer? What is the different between weighting and …

I’m pretty new in data mining but thanks to your great videos and the easy GUI I already feel quite comfortable with the program. However, I’m struggling on using the right operators or in other words I don’t know whether the result that I get is really significant. A short overview on the general types of operators would be so great!

Thanks a million for all your effort you put in your blog and keep posting!!

Kind regards,
Kihmo

By: Tom

Tom — Thu, 13 May 2010 20:48:23 +0000

@Justin: On making a random data generator or do you mean creating your own data files?

By: Justin

Justin — Thu, 06 May 2010 16:18:16 +0000

Thanks for the tutorials, it is great, I have a question, where can i find insight on how to customize or make a new model for data generation?

By: Tom

Tom — Thu, 29 Apr 2010 23:47:29 +0000

@Mark: Ok, I see. Yes, there are algebraic formula’s for all this stuff, some more complicated than others. I remember doing them by hand in my decision analysis classes, it felt like I was being kicked in the crotch repeatedly.

I suggest getting a hold of a good operations research book, it should have the formulas for a lot of what you might be looking for.

By: Mark Knecht

Mark Knecht — Thu, 29 Apr 2010 23:11:17 +0000

Tom – I’m interested in discovering non-genetic, algebraic solutions using RM. I day trade and neural networks aren’t going to play well inside of TradeStation. Personally I’m not comfortable with trying to tie Rapid Miner to TradeStation in a live setup. However if I can mine some solutions that use my technical indicators with some sort of weightings then I can write that back into TradeStation code and backtest what I’m finding in Rapid Miner for accuracy.

As an example on of the first tutorials looks at the Golf sample data and builds a simple decision tree that appears to be completely algebraic/logic oriented. I believe one of your later tutorials looking at marketing data and deciding that certain zip codes and ages made sense to target. I’d like to do models more like that and not neural based, at least for day trading.

Neural networks for multi-day trend trading make lots of sense to me.

By: Tom

Tom — Thu, 29 Apr 2010 10:54:31 +0000

@Mark: Are you referring to the actual formula and theory behind an artificial network? Or are you referring to the parameters in the operators? If you are interested in “refining” the parameters, such as learning rate and/or momentum, you can use the Parameter Optimization operator.

By: Mark Knecht

Mark Knecht — Wed, 28 Apr 2010 17:03:45 +0000

Tom,
This was another good video. Thanks!

One question that keeps coming up for me and possibly will be answered in a later video is what technology is actually in the underlying model? Is it something that has logical rules, or is is something neural network based? I _think_ that this one was logical and the rules could be converted to some other environment, but maybe others are neural and couldn’t be used anywhere else.

Maybe a future video could cover how to mine and extract rules that could be converted to code in another language.

- Mark