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Hello there,
Thank you for your excellent resource. I wondered if I might ask about whether MTAG is sensitive to sex imbalance. I cannot think why this would be, but wanted to make sure.
I have …
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Training of Mask R-CNN in the current implementation can suffer from class imbalance. As all selected training proposals are treated as the same class, objects that are more abundant than others will …
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Perhaps it would be nice to add a feature which would make NH spotlight worker-local latencies/counters, when they significantly diverge from what they look like from a global/aggregated perspective i…
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So, if I wanted to adjust the loss function to account for class imbalance ..... where would I do that? Anyone have any thoughts on compensating for class imbalance in the training data?
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Hi zoogzog,
I'm wondering why to apply tencrop technique on testing images. I thought data augmentation techniques should only be applied on training set in order to add diversity of training image…
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Resource: https://datascience.stackexchange.com/questions/13490/how-to-set-class-weights-for-imbalanced-classes-in-keras
**Criteria for success:**
- Model validation accuracy improves by at least 2%
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Hello, Thank you for the paper and the repo. I was wondering how can I deal with class imbalance during the active learning loop. Do you think the model will be choosing more samples from a class with…
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E. Triantafillou et. al. [1] had experiments for few-shot learning with class imbalance to see if the class imbalance actually impacts to the performance of the few-shot learning methods.
**Resul…
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Take this example:
```
a = DataFrame(a =["a","b","c"], b=[1,2,3])
b = ["a","a","b"]
Xover, yover = random_oversample(a, b)
```
This fails because ` ScientificTypes.schema(X).scitypes` fai…
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The `fix_imbalance_method` does not support `Pipeline` class from `imblearn` package to apply more than one method for fix imbalance.
Does it make sense to apply more the one method of oversampling a…