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## 💥 Proposal
sub issue under issue #187
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There does not appear to be a way to stratify data in ML.NET, is this likely to be implemented anytime soon?
Say I have data that has an uneven predictor field split 90% / 10%, I would like to cr…
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Current k-fold cross-validation assumes that the supplied sample data is uniformly randomized, hence, performs simple slicing of the array for individual folds. We should partition the data in a way t…
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Add new feature: stratified cross validation
This cross-validation is a variation of KFoldIteration that returns stratified folds. The folds are made by preserving the percentage of samples for each …
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Hi there Paul -- first off thanks so much for all your work! I appreciate the improvements to the cross-validation options but I came across an issue :confused:
I am trying to implement "block" cro…
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## 📌 이슈 설명
Age 부분에 Stratified K-Fold Cross Validation을 적용해보려고 합니다.
Age부분의 60대 이상 데이터 비율이 매우 낮아, 이를 적용하는 것이 의미가 있다고 생각합니다.
## 📋 체크리스트
- [x] 관련 문서를 확인했습니다.
## 📎 관련 자료
https://blog.naver.…
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In Chapter2, we had make a training set by using stratified sampling to guarantee that the test set is representative of the overall population. However, in the "Better Evaluation Using Cross-Validat…
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Hi,
I am working on a model with highly imbalanced data which originates from few (as few as 30 observations) observations of species presences and a few thousand randomly selected background obser…
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# CrossValidation 交叉验证
## Reference
- [几种交叉验证(cross validation)方式的比较](https://www.cnblogs.com/ysugyl/p/8707887.html)
- [sklearn - cross validation](https://scikit-learn.org/stable/modules/cro…
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○ Time: 6 weeks
○ Tools Required: Scikit-learn, TensorFlow, PyTorch (within Azure AI Studio or Microsoft Fabric)
○ Steps:
1. Define model requirements and objectives.
□ Utilize histor…
zepor updated
3 weeks ago