-
## Description
Currently, ExplainableAI's LLM-powered explanations provide general insights into model predictions, which are helpful in most cases. However, there is a need for more tailored explana…
-
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…
-
## Feature
Similar to https://github.com/tidymodels/probably/issues/159.
When producing a stacked ensemble of predictions, although the base models may have been trained using importance weights…
-
-
Dear Scimap Team,
Thank you for your exceptional work in advancing spatial-omics biology. I am currently facing a challenge with integrating two different scales of CODEX quantification data proc…
-
Hi,
I have a multi-label dataset with extremely imbalanced classes, are there any developed methods in scikit-multilearn working well on this imbalanced data? thanks.
-
## 論文リンク
https://arxiv.org/abs/1911.02855
## 公開日（yyyy/mm/dd）
2019/11/07
## 概要
単純な cross entropy では、 accuracy のみを見て False Positive, False Negative 両方をケアできてない点、簡単なデータが大量にあったときにそれらの寄与が dominant …
-
Hi,
I experimented with verifying your approach however I didn't receive such low F1 numbers for few shot. In looking at data_full, banking has the same amount of training samples as all other do…
-
# Tweet summary
Adjust probability bias due to sampling for imbalanced data
# Useful link
https://pompom168.hatenablog.com/entry/2019/07/22/113433
-
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…