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### 🚀 The feature, motivation and pitch
The addition of weighted loss functions to the PyTorch library, specifically Weighted Mean Squared Error (WMSE), Weighted Mean Absolute Error (WMAE), and Weigh…
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Hey, is it possible to generate the balanced synthesized data even though the realtabformer model is trained on imbalanced data (the proportion is even up to 4 to 96). How do I do that?
CTGAN, TVAE…
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### Deep Learning for Imbalance Classificaition
#### Survey
1. [A systematic study of the class imbalance problem in convolutional neural networks
Cost-Sensitive](https://arxiv.org/pdf/1710.05381.p…
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### Question
Hi,
I use yolov5x with this setting (train: 70%, val: 10%, test: 20%)
```
train: images/train # train images (relative to 'path') 128 images
val: images/val # val images (relativ…
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Hi. I am trying to understand how to use the schema filtering part. From the given entire schema of the database, how can I get the relevant tables and columns required for a given NL query? How shoul…
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# Building a multiclass classification model | Practical Cheminformatics
Data cleaning, adding structures to PubChem data, building a multiclass model, dealing with imbalanced data
[https://patwalte…
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Consider adding an option to handle for imbalanced data https://github.com/scikit-learn-contrib/imbalanced-learn.
It can be implemented in similar way as the `Golden Features` step.
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Related: #20
Currently no measure is computed that's useful for highly imbalanced classes.
Take for example sick:
https://www.openml.org/t/3021
I would like to see the "mean" measures be compu…
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My data set is imbalanced; I understand from the [Interpreting Tree Ensembles with inTrees](https://arxiv.org/pdf/1408.5456v1.pdf) that Error = accuracy.
In an imbalanced set Error rate is not ver…
ghost updated
6 years ago
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