I’m working on a multi label classification problem that each data frame has a unit of 1-5 as values in it, which loss function would be the best to use in this scenario?

[image] Rexedoziem: multi label classification problem that each data frame has a unit of 1-5 as values in it I’m not sure how to understand this description, but assume you are working on a multi-label classification where each sample can belong to 0, 1, or multiple classes. If so, you can u…

That’s the screenshot of the problem. I’m asking if the values in the targets, since it’s not zeros and ones, can I still use BCEloss…

No, I don’t think the labels represent a multi-label classification, but rather some kind of scores. In that case you might want to use a regression loss such as nn.MSELoss.

So it can be treated as multioutput regression problem where it’ll having the number of classes as outputs?

[image] Rexedoziem: where it’ll having the number of classes as outputs No, I don’t think your current targets represent classes, as they are floating point numbers. E.g. what would “cohesion 2.5; synta… 2.5” represent?

But in this case the problem can be treated as multioutput regression problem?

Maybe I can screenshot the full data for you to see it……

[image] Rexedoziem: can be treated as multioutput regression Yes, the use case can be treated as a regression with multiple outputs. I would not claim they are classes: [image] Rexedoziem: treated as multioutput regression problem where it’ll having the number of classes as outputs

But can I place the 6 targets into the forward function?, and how does that look like…. Then talking about the loss function should I add all the losses to get the final loss?

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Multi label classification problem

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Rexedoziem (Rexedoziem) September 3, 2022, 10:27pm 3