"Multi-class Classification using SVM"

D_MD_M Member Posts: 15  Maven
edited May 23 in Help
Hi,

I want to classify data into positive, negative & neutral.

For this I want to use 2 SVM one trained on positive & not positive data & the other on negative & not negative data. Now I want to take the data predicted as positive by the 1st classifier & not negative by the second classifier as positive & data predicted as negative by the 2nd classifier & not positive by the 1st classifier as negative. In rest of the cases I want to tag the data as neutral.

Is it possible to do this in Rapid-Miner in GUI Mode?
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Answers

  • fischerfischer Member Posts: 439  Guru
    Hi D.M.,

    please look at the AttributeConstruction operator. You can use the if(condition,thenValue,elseValue) function to construct your target attribute based on the two other predictions.

    Best,
    Simon
  • D_MD_M Member Posts: 15  Maven
    Thanks for replying.

    I am very new to rapidminer. Can u plez explain a bit more? I am not able to put the 2 classiifers under the same root process.  Can you please tell how can I put the 2 classifers under the same root process?
  • fischerfischer Member Posts: 439  Guru
    Dear D.M.,

    that depends very much on how your data looks like and what you want to achieve. A general approach would be the following:

    - Use an AttributeConstruction to generate "isPositiv" and "isNegative" binary attribute
    - Declare the first as a label (ChangeAttributeRole)
    - Train a model
    - Set the second as a label
    - Train another model
    - Then, apply both models subsequently to the test set, and perform the inverse attribute construction on the two prediction attributes you get.

    I would recommend to have a look at the RapidMiner training courses. E.g., an introductory course is this one: http://rapid-i.com/content/view/110/143/lang,en/

    Best,
    Simon
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