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[R-package] abess fails with one feature #493

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sebffischer opened this issue Mar 1, 2023 · 2 comments
Closed

[R-package] abess fails with one feature #493

sebffischer opened this issue Mar 1, 2023 · 2 comments
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@bbayukari
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@sebffischer
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Describe the bug

abess::abess() from R package fails when there is only one feature.

Code for Reproduction

library(abess)
library(data.table)

x = data.table(x = sample(100, size = 100))
y = factor(sample(c("a", "b", "c"), size = 100, replace = TRUE))

abess(x = x, y = y, family = "multinomial")
#> Error in Matrix::Matrix(x[, -y_dim], sparse = TRUE, dimnames = list(vn, : length of 'dimnames' [1] not equal to array extent

Created on 2023-03-01 with reprex v2.0.2

Version: ‘0.4.7’

This did not happen in previous releases (you broke the CI of mlr3extralearners)
sebffischer added a commit to mlr-org/mlr3extralearners that referenced this issue Mar 1, 2023
@sebffischer
tests(abess): disable failing test for abess classif learner
53a8a62 
This was not a issue previously and might have been introduced
in abess 0.4.7

abess-team/abess#493
@Mamba413 Mamba413 added the bug Something isn't working label Mar 2, 2023
bbayukari added a commit to bbayukari/abess that referenced this issue Mar 2, 2023
@bbayukari
fix: abess fails with one feature abess-team#493
7971590
sebffischer added a commit to mlr-org/mlr3extralearners that referenced this issue Mar 6, 2023
@sebffischer
fix: add missing parameters (#269)
70159f4 
* feat: add missing parameters

Due to changes in the package "dbarts" and "survivalmodels"
the parameter tests started to fail.
This adds the missing parameters

* fix: remove weights parameter from dbarts

The predict and the train method of the dbarts algorithm have
the "weights" parameter and it is not fully clear to me,
how they influence the training, because the predict and
train weights parameter have the same documentation (?)
For that reason exclude it from the paramtest and fix
if someone raises an issue

* tests(abess): disable failing test for abess classif learner

This was not a issue previously and might have been introduced
in abess 0.4.7

abess-team/abess#493
@bbayukari
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Hey, we have fixed this issue and the code for reproduction has been able to pass. We will soon publish a new abess version to completely address this issue.

Is there something else shall we do?

@sebffischer
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Thanks!
No thats it :)

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@sebffischer @Mamba413 @bbayukari