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LudvigOlsen
R Package: Cross-validate one or multiple gaussian or binomial regression models at once. Perform repeated cross-validation. Returns results in a tibble for easy comparison, reporting and further anal...
Hej L, I'm using your functions to visualize a multiclass confusion matrix and it gives me issues when some of the categories are never predicted for some of the targets....
Probably second to last issue (I'll be trying tomorrow the batch function). What about including Poisson regression (outcome is a count variable)? That's the third most common form of regression...
Dear @LudvigOlsen , As of today, the following doesn't seem to be supported any more: plot_confusion_matrix( conf_mat, font_row_percentages=font(prefix=c("NPV = ", "", "", "PPV = ")), font_col_percentages = font(prefix=c("Spec = ",...
`max_fixed_effects = 1` should be allowed. Also multiple dependent variables. ``` combine_predictors("y2", c("x1", "x2"), max_fixed_effects = 1, max_interaction_size = 0) ## Error in combine_predictors("y2", c("x1", "x2"), max_fixed_effects = 1, :...
Suggest that the *core packages* identified in the [CRAN Machine Learning Task View](https://cran.r-project.org/web/views/MachineLearning.html) be provided out-of-the-box. These are listed near the bottom of the Task View as Core and are...
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R Package: Cross-validate one or multiple gaussian or binomial regression models at once. Perform repeated cross-validation. Returns results in a tibble for easy comparison, reporting and further anal...