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How do I deal with different class sizes when classifying data with a petternnet?

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Anne Bernhart 2021-3-17

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评论： Anne Bernhart 2021-3-27

采纳的回答： Shravan Kumar Vankaramoni

I want to classify datasets using a patternnet. I have 2 classes (labelled 1 and 2). However, class 2 is significantly smaller than class 1 (ratio 1:9). The patternnet always classifies every sample into class 1, reaching 90% accuracy with it.

Is there any way to weigh or prioritize my classes so that this is not viewed as the best solution? (e.g. a cost matrix like for a decision tree (fitctree))

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MaHa 2021-3-17

I see I misunderstood sorry. What happens if you reduce the number of labbelled 1 to the number of labbelled 2 ? Does it still classes everything in L1 ?

Anne Bernhart 2021-3-17

If I do that it works fine but I would prefer including all of my data.

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Shravan Kumar Vankaramoni 2021-3-25

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Hi Anne,

Have a look at the below thread. Hope that answers your question

https://www.mathworks.com/matlabcentral/answers/501704-handling-imbalanced-data-with-patternnet

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Anne Bernhart 2021-3-27

thank you very much! That is exactly what I was looking for :)

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