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I would like to know the exact expression of multi:softprob in terms of probabilities and labels. What is the difference between multi:softprob and mlogloss? Can I use the mlogloss objective function …
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Could you clarify whether your model functions as a multi-label classifier with a large number of classes? If not, would you mind elaborating on the advantages of your model compared to a multi-label …
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Dear Zhou,
Thank you for sharing Dassl!
I encounter some problem when implementing 'coop' with multi-label classification.
My label in One-hot presentation is like: [0,1,0,1,0,0,0,1], so how to d…
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### MOA Multi-label Classification Predictions
@gway @shntnu
- A compound profile has multiple MOAs i.e. more than one target label (multi-label classification)
- All MOAs found in just on…
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Hey there,
As tpot seems to rely solely on scikit-learn for (meta-) estimators the lack of extended multi-label classification strategies is quite noticeable. The work on some of the strategies and a…
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How would I modify run_classifier.py in order to get it to do multi class classification? What I mean by that is an item in the dataset can belong to more than 1 class - not just one class. For exampl…
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Hello,
I'd like to report two issues regarding classification tasks in modnet:
First, the loss function passed to `ModnetModel().fit()` is overwritten with `"categorical_crossentropy"` if `val_d…
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Vgg16 model using 6714 annotated images. 20k train image sample size, 0.2 validation fraction, (224,224) image size.
lr = 0.01, epsilon = 0.1, 50 epochs
in confusion matrices the columns are pr…
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I am trying to train an image classifier where image ground truth contains multiple classes. Is it possible to train a model that outputs multiple classes?
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### Search before asking
- [X] I have searched the Ultralytics YOLO [issues](https://github.com/ultralytics/ultralytics/issues) and [discussions](https://github.com/ultralytics/ultralytics/discussion…