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In the finetune phase, the whole dataset is used which will cause over fitting for the model...
So, I think this can be solved by:
- divide the dataset into training, test & validation sets
- Or, usin…
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I've built the [ParetoSmooth.jl](https://github.com/ParadaCarleton/ParetoSmooth.jl) package for fast approximate LOO cross-validation. The function currently only works with cross-entropy loss. (Bayes…
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Hi,
I have adapted the code of multiclass SVM to my dataset, it is working well, however I don't know how to use k-fold cross validation in the training loop. Any help or guidance would be very appr…
ilame updated
6 years ago
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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…
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If labels are highly imbalanced (for example, TP53 in ovarian cancer) ROC can break because some cross-validation splits will only have one class.
Maybe using [StratifiedKFold](https://scikit-learn…
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I compiled and configured the Petsc with `petsc_configure.sh` script, which was successfully done. After that I moved to `src` folder and run the `buildAll.sh` script to compile the mlsvm, but I got t…
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### Description
Cross-validation
### Purpose
cross-validation is useful for simulating replicability (see Koul, Becchio, & Cavallo, 2018)
### Use-case
for testing robustness of model ac…
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In the previous version of turicreate (graphlab-create-2.1) were a [cross validation module](https://turi.com/products/create/docs/graphlab.toolkits.cross_validation.html) that included cross_validati…
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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 months ago