tests/testthat/_snaps/sparsevctrs.md

In tidymodels/parsnip: A Common API to Modeling and Analysis Functions

sparse tibble can be passed to `fit() - supported

Code
  xgb_fit <- fit(spec, avg_price_per_room ~ ., data = hotel_data)
Condition
  Error in `fit()`:
  ! Sparse data cannot be used with formula interface. Please use `fit_xy()` instead.

sparse tibble can be passed to `fit() - unsupported

Code
  lm_fit <- fit(spec, avg_price_per_room ~ ., data = hotel_data[1:100, ])
Condition
  Warning:
  `data` is a sparse tibble, but `linear_reg()` with engine "lm" doesn't accept that. Converting to non-sparse.

sparse matrix can be passed to `fit() - supported

Code
  xgb_fit <- fit(spec, avg_price_per_room ~ ., data = hotel_data)
Condition
  Error in `fit()`:
  ! Sparse data cannot be used with formula interface. Please use `fit_xy()` instead.

sparse matrix can be passed to `fit() - unsupported

Code
  lm_fit <- fit(spec, avg_price_per_room ~ ., data = hotel_data[1:100, ])
Condition
  Warning:
  `data` is a sparse tibble, but `linear_reg()` with engine "lm" doesn't accept that. Converting to non-sparse.

sparse tibble can be passed to `fit_xy() - unsupported

Code
  lm_fit <- fit_xy(spec, x = hotel_data[1:100, -1], y = hotel_data[1:100, 1])
Condition
  Warning:
  `x` is a sparse tibble, but `linear_reg()` with engine "lm" doesn't accept that. Converting to non-sparse.

sparse matrices can be passed to `fit_xy() - unsupported

Code
  lm_fit <- fit_xy(spec, x = hotel_data[1:100, -1], y = hotel_data[1:100, 1])
Condition
  Error in `fit_xy()`:
  ! `x` is a sparse matrix, but `linear_reg()` with engine "lm" doesn't accept that.

sparse tibble can be passed to `predict() - unsupported

Code
  preds <- predict(lm_fit, sparse_mtcars)
Condition
  Warning:
  `x` is a sparse tibble, but `linear_reg()` with engine "lm" doesn't accept that. Converting to non-sparse.

sparse matrices can be passed to `predict() - unsupported

Code
  predict(lm_fit, sparse_mtcars)
Condition
  Error in `predict()`:
  ! `x` is a sparse matrix, but `linear_reg()` with engine "lm" doesn't accept that.

sparse data work with xgboost engine

Code
  xgb_fit <- fit(spec, avg_price_per_room ~ ., data = hotel_data)
Condition
  Error in `fit()`:
  ! Sparse data cannot be used with formula interface. Please use `fit_xy()` instead.

to_sparse_data_frame() is used correctly

Code
  fit_xy(spec, x = mtcars[, -1], y = mtcars[, 1])
Condition
  Error in `to_sparse_data_frame()`:
  ! x is not sparse

Code
  fit_xy(spec, x = hotel_data[, -1], y = hotel_data[, 1])
Condition
  Error in `to_sparse_data_frame()`:
  ! x is spare, and sparse is not allowed

Code
  fit_xy(spec, x = hotel_data[, -1], y = hotel_data[, 1])
Condition
  Error in `to_sparse_data_frame()`:
  ! x is spare, and sparse is allowed

maybe_sparse_matrix() is used correctly

Code
  fit_xy(spec, x = hotel_data[, -1], y = hotel_data[, 1])
Condition
  Error in `maybe_sparse_matrix()`:
  ! sparse vectors detected

Code
  fit_xy(spec, x = mtcars[, -1], y = mtcars[, 1])
Condition
  Error in `maybe_sparse_matrix()`:
  ! no sparse vectors detected

Code
  fit_xy(spec, x = as.data.frame(mtcars)[, -1], y = as.data.frame(mtcars)[, 1])
Condition
  Error in `maybe_sparse_matrix()`:
  ! no sparse vectors detected

Code
  fit_xy(spec, x = tibble::as_tibble(mtcars)[, -1], y = tibble::as_tibble(mtcars)[,
    1])
Condition
  Error in `maybe_sparse_matrix()`:
  ! no sparse vectors detected

we don't run as.matrix() on sparse matrix for glmnet pred #1210

Code
  predict(lm_fit, hotel_data)
Condition
  Error in `predict.elnet()`:
  ! data is sparse

fit() errors if sparse matrix has no colnames

Code
  fit(spec, avg_price_per_room ~ ., data = hotel_data)
Condition
  Error in `fit()`:
  ! `x` must have column names.

tidymodels/parsnip documentation built on Feb. 19, 2025, 2:10 a.m.