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

"Weighted Word List based Text Classification"

mrfarhankhanmrfarhankhan Member Posts: 14 Contributor II
edited June 2019 in Help
Hi.

I have a query regarding Text Classification.

I have a list of words with the following 3 attributes. word, weight, class. The class can be positive or negative. Weight is between -1 to 1.

How can I train a classifier like SVM using this word list to classify unseen documents?

Any sample process will be a great help.

Thanks
Farhan!
Tagged:

Answers

  • mrfarhankhanmrfarhankhan Member Posts: 14 Contributor II
    Anyone ???
  • MartinLiebigMartinLiebig Administrator, Moderator, Employee-RapidMiner, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,533 RM Data Scientist
    Hi,

    i am not sure if you can do it the way you want to do it. Usually for classification you have a Bag of Words (with TF/IDF or so) like this 

    word1	word2	word3	label
    1		2		1		true	
    1		4		1		false


    and then you learn on this. This is not the case for you. However, you can have a look on this thread: http://rapid-i.com/rapidforum/index.php/topic,8638.0.html there was a similar question with a dictionary. You can use a similar process like i have shown there. You just need to get the weights in (don't just use one example, but all).

    Cheers,

    Martin
    - Sr. Director Data Solutions, Altair RapidMiner -
    Dortmund, Germany
Sign In or Register to comment.