mlr3filters
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mlr-org
Filter-based feature selection for mlr3
Adding Gaussian Covariance 'filter' from the package https://cran.r-project.org/web/packages/gausscov/gausscov.pdf. I am getting error when running test and examples but can't figure out why. ``` Error in .__Param__assert(self = self, private =...
```r library("mlr3filters") flt("auc")$hash #> Error in mget(private$.extra_hash, envir = self) : invalid first argument ``` introduced by https://github.com/mlr-org/mlr3filters/pull/156 @mllg
Hello there, I want to run a number of machine learning algorithms with different feature selection methods on survival data using the MLR3 package. For that, I am using the...
the importance filter by default uses the "featureless" learner by default, which makes the filter basically useless. There are likely very few cases in which the user wants to initialize...
This part is heavily underdocumented. I would suggest adding mlr3pipelines to `Suggests` to be able to link to `PipeoFilter` and also add examples in the R docs and Readme.
`FilterAUC` operates on features with missing values by just ranking the missing values last (default in `rank()`). I'm not sure that this is statistically sound. I'd suggest removing them and...
# Filters ## Pkg ### _No pkg_ - [x] AUC - [ ] generic permutation - [x] univariate.model.score ### _stats_ - [x] anova - [x] kruskal - [x] linear.correlation -...
Similar to the ones implemented in _mlr_. Blocked by #22.
"This embedded method is based on a perceptron, a type of artificial neural net-work that can be seen as the simplest kind of feedforward neu-ral network, namely, a linear classifier....