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As mentioned in the following paper of Neural Subgraph Matching paper [https://arxiv.org/abs/2007.03092](url) , the dataset distribution of the imbalanced data is 3:1 (negative_sample: positive_sampl…
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In this issue we'll discuss how to clean the data, what's needed and actions.
Please share your thoughts in the comments
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Hello @kingfengji:
Accuray is not make sense in imbalanced data.
How could I change evaluation like recall or precision?
Thanks.
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G-mean is widely used in classification problems with imbalanced data and has proven to be worthful metric.
I suggest You to add it to the Catboost library.
Unn20 updated
9 months ago
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The What-If Tool seems really useful.
However for imbalanced data, additional metrics would be great. Being able to use to use Precision-Recall Curves instead of ROC would be amazing. F0.5 Score an…
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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…
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Hi, @chhylp123
We are currently attempting to assemble a hexaploid using hifiasm with the following command:
```
hifiasm -t 100 -l3 --n-hap 6 --dual-scaf --ul ${ont} --h1 ${hic1} --h2 ${hic2} ${…
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I was working on an imbalanced problem with your code for a week and the results got me frustrated with low accuracy. However, after I did some work as below the accuracy has significantly improved so…
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library(h2o)
h
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Hi, thank you for your great work. I am currently exploring the semi-supervised semantic segmentation works, and find your work very interesting.
I want to ask a general question, that is, how to u…