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I am trying to solve a simple classification problem where the label has 12 different levels and need to classify each example into one of these 12. However, I want my output to look like refer the image:

https://i.stack.imgur.com/49USG.png

Here; assuming that I set a confidence threshold of 20%; I want my output to contain all the labels for each id which are above 20% and ordered (highest confidence first). If none of the labels are above 20%; then a default label. More specifically, are there any existing operators in Rapidminer which could give such an output?

Patlolla Vishwarath Reddy
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1 Answers1

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Whenever the Apply Model operator runs, it produces new special attributes corresponding to confidences for the individual values of the label attribute. So if the label has values one, two, three, three new attributes will be created confidence(one), confidence(two), confidence(three). It would be possible to use the Generate Attributes operator to work out some logic to decide how to really classify each example. It would also be possible to use the Apply Threshold operator (with Create Threshold) to do something similar. It's impossible to give any more guidance unless you post a representative example with data.

Andrew Chisholm
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