The output for test failures is very noisy, making it hard to spot the actual failures amidst all the messages.
test_check("extratests", reporter = "summary")
parsnip-extension-messaging: ....Loading required package: survival
...................
S3-registration: ......
butcher-recipes:
Attaching package: 'Matrix'
The following objects are masked from 'package:tidyr':
expand, pack, unpack
....
encodings-glmnet: Loaded glmnet 4.1-8
.........
encodings-randomForest: ......
encodings-ranger: ......
engine-parameters-c5: ..! The Gaussian process model is being fit using 3 features but only has 3
data points to do so. This may cause errors or a poor model fit.
! The Gaussian process model is being fit using 3 features but only has 4
data points to do so. This may cause errors or a poor model fit.
....! The Gaussian process model is being fit using 3 features but only has 3
data points to do so. This may cause errors or a poor model fit.
! The Gaussian process model is being fit using 3 features but only has 4
data points to do so. This may cause errors or a poor model fit.
..
engine-parameters-earth: ..! The Gaussian process model is being fit using 2 features but only has 3
data points to do so. This may cause errors or a poor model fit.
..
The output for test failures is very noisy, making it hard to spot the actual failures amidst all the messages.