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The idea would be to create a function `crossval(x, ...)` that takes a machine learning model as an input and allows users to evaluate the model's performance across k splits of an evaluation data set…
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Cross validation : training data 와 validation data 를 분할하여 특정 데이터에 의존성이 낮은 ,
즉 일반화 성능이 좋은 모델 학습시키기.
가장 널리 사용되는 교차 검증 방법은 k-겹 교차검증(k-fold cross-validation)으로 k는 특정 숫자인데 보통 5또는 10을 사용. 분류기의 일반화 성능…
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The function groupKFold in caret 6.0-86 does not return the requested number of folds, even though it is possible according to the number of groups. caret version 6.0-84 returns the correct number of …
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Thanks for sharing this excellent work. I am quite curious about your evaluation on SentEval. You report in the paper that all your evaluations on SentEval are based on 10-fold cross-validation, but i…
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Dear Jianwei,
Thank you for your contribution to medical image segmentation research with this paper. I am trying to reproduce your model and I have a question regarding the train, validation, and t…
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Hi there
Wonderful idea that you have implemented. I was wondering if it would be possible to perform K-Fold cross validation?
Thanks
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## Context
Improvements to bootcamp flow
## Detailed Description
SLU08 has
```
Using the Metrics
Hold-out method
Training error
Testing error
K-Fold
…
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Need materials with example codes on various performance metrics in Machine learning,
Here are some of them,
- StratifiedFold
- K Fold Cross validation
- Confusion Matrix
- Precision
- R…
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Voortgang afgelopen week:
- K-fold cross validation geimplementeerd
- performance verbeterd (F1 score van ongeveer 0.80 naar 0.95)
- beginnetje gemaakt aan methodology sectie van het verslag
Pla…
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For example,
``` r
dat [1] "Using 19 cores for parallelization."
#> [1] "Finished EFAs. Starting CFAs"
lavaan::lavInspect(x$cfas[[1]][[1]], "options")$missing
#> [1] "listwise"
```
Created…