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In order to reduce overfitting, I would like to ask for a new parameter: "n_repetitions". This parameter sets the number of complete sets of folds to compute for repeated k-fold cross-validation.
C…
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Current SER evaluation only split into five cross-validation using KFold. It is necessary to split based on session, use each session for test, and report average score (UA, WA) for benchmarking.
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Currently, `loo` and `kfold` facilitate model comparison for models without a time dependency. To my knowledge, brms does not support time-series cross-validation in the same way. Are methods such as …
ghost updated
4 years ago
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**Here is the section of code that is giving me an error, not sure how to fix it**
# initalise cross_val kfold (stratified)
cv = cb.cross_val.kfold(model=cb.model.PLS_SIMPLS, #…
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Hi I got the following error, can you help me ?
CMD: optimize_augustus.pl --species="arabidopsis" --rounds=5 --cpus=0 --kfold=0 --onlytrain=training.gb.onlytrain genes.gb.train.train > optimize.out…
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Hello, the cross-validation method used in this paper is to use 1-Kold as the training set and the rest as the test set. I want to know that if "For test, train in kfold. Split (train_images, train_la…
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### Describe the workflow you want to enable
What roughly happens in cross-validation as of now:
```
# k-fold cross validation
scores = list()
kfold = KFold(n_splits=10, shuffle=True)
# e…
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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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In the code, Kflod cross-validation divides the data set. Each time the code is divided into …
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As a user, I want to be able to assign arbitrary data properties to my bandit jobs using python dot notation.
for example, i might want to record statistical performance metrics for a model like th…