The Altair Community is migrating to a new platform to provide a better experience for you. In preparation for the migration, the Altair Community is on read-only mode from October 28 - November 6, 2024. Technical support via cases will continue to work as is. For any urgent requests from Students/Faculty members, please submit the form linked here
"Error=Order of attributes is not equal for training and application example set"
wotsiznamiz
Member Posts: 9 Contributor II
I am running a text-mining model... I have two different text data sets -- one for building the model and one for validating.
When I attempt to load the model and apply it to my validation test set, I notice the following error message...
[Warning] Kernel Model: The order of attributes is not equal for the training and the application example set. This might lead to problems for some models.
Does anyone have any idea why I'm getting this error message?
When I attempt to load the model and apply it to my validation test set, I notice the following error message...
[Warning] Kernel Model: The order of attributes is not equal for the training and the application example set. This might lead to problems for some models.
Does anyone have any idea why I'm getting this error message?
Tagged:
0
Answers
first, i never got this message in rapindminer so i m just going to give you a general advice that i follow.
it is a warning so i would ignore it. before ignoring it completely, i would manually check the datasets to be sure everything is ok.
in the case of those kind of messages i would first check if the warning comes from a difference in the way the datasets are written, i would check to be sure the label is correctly chosen in both datasets and if i m still unsure, i would try to use a "leave one out" or k cross fold validation, and if the performance is the same as using the test dataset, then everything is ok.
but generally i ignore the warnings.
in general this is right: most warnings are not errors and can often be ignored. Here I would like to add that in the case of text mining it is important to save the wordlist during training and re-use during model application. Did you do that?
Cheers,
Ingo