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We have to handle class imbalance. One of the methods is multiplying the rows with rare classes to equalize the class frequency in train dataset.
Add the proper method and expand the interface to …
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Could you update the codes of SelectNet, proposed in the article **SelectNet: Learning to Sample from the Wild for Imbalanced Data Training**?
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Due to the simple fact that we can, in theory, remove competing R groups from an equation, and thereafter balance the mass of the equation, we do have the problem, such as with fatty-acyl-ACPs, that w…
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Hi there, great paper. I can't seem to find the original dataset - it may have restricted access. Do you know where we can find the data?
Also, would you consider training on a more imbalanced datase…
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- Due to computational restrictions, we only used 10% of our dataset.
- Even our best model does not give best performance
- class imbalance
- too many false positives, need a measure to deal with …
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Here are some input query strings and the results of parsing them, including the error, if any. Some of them should result in parse errors but do not.
```
( -> (query: missing close paren, got t…
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Hi,
I frequently use ANGSD to make Fst calculations and I recently tried a calculation on a subset of my data where I have 6 populations, but in this instance I happen to have only 1 individual from …
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Approach I'd take :- 1. Utilizing 5 models such as DenseNet121 , Xception, VGG16, ResNet50, and InceptionV3 for image classification.
2. Applying data augmentation (rotation, zooming, flipping,…
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Thanks so much for your implementation. But I have several questions:
1) In the below picture, it seems that the class with less numbers is sampled repeatedly, while the class with more numbers is s…