Code
.convert_form_to_xy_fit(rate ~ ., data = Puromycin_miss, na.action = na.fail,
indicators = "traditional", remove_intercept = TRUE)
Condition
Error in `na.fail.default()`:
! missing values in object
Code
expected <- glm(class ~ ., data = hpc, x = TRUE, y = TRUE, family = binomial())
Condition
Warning:
glm.fit: fitted probabilities numerically 0 or 1 occurred
Code
.convert_form_to_xy_fit(mpg ~ ., data = mtcars, composition = "tibble",
indicators = "traditional", remove_intercept = TRUE)
Condition
Error:
! `composition` should be either "data.frame", "matrix", or "dgCMatrix".
Code
.convert_form_to_xy_fit(mpg ~ ., data = mtcars, weights = letters[1:nrow(mtcars)],
indicators = "traditional", remove_intercept = TRUE)
Condition
Error:
! `weights` must be a numeric vector.
Code
.convert_xy_to_form_fit(mtcars$disp, mtcars$mpg, remove_intercept = TRUE)
Condition
Error:
! `x` cannot be a vector.
Code
.convert_xy_to_form_fit(mtcars[, 1:3], mtcars[, 2:5], remove_intercept = TRUE)
Condition
Error in `.convert_xy_to_form_fit()`:
! `x` and `y` have the names "cyl" and "disp" in common.
i Please ensure that `x` and `y` don't share any column names.
Code
parsnip::maybe_matrix(ames[, c("Year_Built", "Neighborhood")])
Condition
Error in `parsnip::maybe_matrix()`:
! The column "Neighborhood" is non-numeric, so the data cannot be converted to a numeric matrix.
Code
parsnip::maybe_matrix(Chicago[, c("ridership", "date")])
Condition
Error in `parsnip::maybe_matrix()`:
! The column "date" is non-numeric, so the data cannot be converted to a numeric matrix.
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