"How to store (within-process) feature-selected attributes?"

alimay

Hi.. My question is simple and even though i think a lot of people must've faced it, i could not find a solution on the web. Here it is:

I have a file which after importing I split into two using the split operator. Then on the first partition I do a feature selection and model construction, and I keep the second partition for test set purposes. Now the thing is: I need a way to remember/store the feature-selected attributes so that I can select them by using select attributes operator, when I apply my model to the test, so that I do not get the error:

May 1, 2011 6:03:32 AM WARNING: SimpleDistribution: The number of regular attributes of the given example set does not fit the number of attributes of the training example set, training: 50, application: 3045

So what I need is something like a "group attributes" operator, that will group the attributes coming from the feature selection operator I use (and give it a user-defined name like "grouped attributes"). Later when I use select attributes operator on the test set, it should display, in addition to all regular attributes and class attibute, this "grouped attributes" so that I can select it.. Otherwise I need to note all the attributes coming from the feature selection and select them one by one, which is a terrible experience if you're trying to select the best few hundred attributes.

Is there already an operator doing this? I failed to see.
I hope my question is clear. Thank you in advance for your answers.

haddock

Hi there,

In similar circumstances I use the attribute weights that the thinning operator produces, either diectly or read them back from file, and then apply them to another dataset. Should work.

Hope so!