"Weighted Word List based Text Classification"

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

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.



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    mrfarhankhanmrfarhankhan Member Posts: 14 Contributor II
    Anyone ???
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    MartinLiebigMartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,517 RM Data Scientist

    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).


    - Sr. Director Data Solutions, Altair RapidMiner -
    Dortmund, Germany
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