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None
quantile_normalize()
.check_duplicate_rows()
.extract_tunable_params()
.plot_regression_predictions()
.None
plot_regression_residuals()
to
plot the residuals.plot_regression_predictions()
to plot the predictions from the function
extract_wflw_predictions()
load_deps()
fast_regression()
and
fast_classification()
to drop NULL predictions.None
extract_regression_residuals()
.drop_na
to
fast_classification()
and
fast_regression()
.discrim
mda
sda
sparsediscrim
liquidSVM
kernlab
klaR
internal_make_wflw_predictions()
to include all data
magrittr
from Imports
of
DESCRIPTION
file from #150.internal_make_spec_tbl()
now adds a class to
each model_spec
created by parsnip
, for
example, a gee
engine setting using
linear_reg()
will return an extra class of
gee_linear_reg
gee
, glmnet
, and
rules
to the core_packages()
function.create_model_spec()
tidyaml_base_tbl
to the output of
create_model_spec()
internal_set_args_to_tune()
to use
dplyr::pick()
instead of dplyr::cur_data()
since it was deprecated.internal_set_args_to_tune()
to use
!names(new_mod_args)
instead of !names(.)
tidymodels::tidymodels_prefer()
internal_make_wflw_gee_lin_reg()
full_internal_make_wflw
fast_classification()
and
fast_regression()
to use
full_internal_make_wflw()
None
create_model_spec()
function.create_model_spec()
internal_make_wflw_predictions()
to use
recipes::testing()
instead of
recipes::training()
None
make_regression_base_tbl()
make_classification_base_tbl()
internal_make_spec_tbl()
internal_set_args_to_tune()
create_workflow_set()
get_model()
extract_model_spec()
extract_wflw()
extract_wflw_fit()
extract_wflw_pred()
match_args()
fast_classification_parsnip_spec_tbl()
and fast_regression_parsnip_spec_tbl()
to use the
make_regression and
make_classification functions.fast_classification_parsnip_spec_tbl()
and
fast_regression_parsnip_spec_tbl()
to use the
internal_make_spec_tbl()
function.internal_make_spec_tbl()
fast_classification_parsnip_spec_tbl()
fast_classification()
None
None
core_packages()
install_deps()
, and load_deps()
None
None
fast_regression_parsnip_spec_tbl()
create_splits()
fast_regression()
create_model_spec()
internal_make_wflw()
,
internal_make_fitted_wflw()
,
internal_make_wflw_predictions()
None
None
NEWS.md
file to track changes to the
package.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.