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Adding separate PipeOpPreproces function is required to create columns with the information where imputation will happen. I will do this. This issue is only to inform you about the problem with the cu…
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### Expected Behaviour
Benchmarking to complete for a competing risks model
### Actual Behaviour
`Error in dimnames(x) Loading required package: mlr3
library(mlr3extralearners)
#>
#> Attachi…
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### Algorithm
Generalized additive model
### Package
mgcv
### Supported types
* [ ] classif
* [ ] regr
* [x] surv
* [ ] dens
### I have checked that this is not already implemente…
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### Algorithm
### Package
### Supported types
* [ ] classif
* [ ] regr
* [ ] surv
### I have checked that this is not already implemented in
* [ ] mlr3
* [ ] mlr3learners…
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Problem:
catboost version: R package 0.24.1
Operating System: Windows
CPU: Intel Core i7
The R version does not seem to support sparse matrices Matrix::sparseMatrix().
Would be really great if…
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Hello,
I am going through the mlr3book and in Section 3, Exercise 3 the penguins_simple task is not available anymore i guess:
Error: Element with key 'penguins_simple' not found in DictionaryTask…
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After dealing with the idea of caching in [mlr](https://github.com/mlr-org/mlr/pull/2463) recently, I think this is an important topic for _mlr3_.
It would be a core base feature and should be integr…
pat-s updated
3 years ago
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Is there a way to set `return_one` to `FALSE` in `PipeOpMice`, so that I get `m` different imputed datasets? And then how do I feed each imputed dataset into a learner to train m separate models in th…
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I keep encoutnering the following error wen running SSVM jobs in the batchtools/batchmark setting, specifically _after_ the tuning process appears to have completed without major issues:
```r
# ..…
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