An extensible framework to create and preprocess design matrices. Recipes consist of one or more data manipulation and analysis "steps". Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting design matrices can then be used as inputs into statistical or machine learning models.
recipes
0.1.3.9002Several argument names were changed to be consistent with other tidymodels
packages (e.g. dials
) and the general tidyverse naming conventions.
K
in step_knnimpute
was changed to neighbors
. step_isomap
had the number of neighbors promoted to a main argument called neighbors
step_pca
, step_pls
, step_kpca
, step_ica
now use num_comp
instead of num
. , step_isomap
uses num_terms
instead of num
.step_bagimpute
moved nbagg
out of the options and into a main argument trees
.step_bs
and step_ns
has degrees of freedom promoted to a main argument with name deg_free
. Also, step_bs
had degree
promoted to a main argument.step_BoxCox
and step_YeoJohnson
had nunique
change to num_unique
.bake
, juice
and other functions has newdata
changed to new_data
. For this version only, using newdata
will only result in a wanring.na.rm
changed to na_rm
.prep
and a few steps had stringsAsFactors
changed to strings_as_factors
.add_role()
can now only add new additional roles. To alter existing roles, use update_role()
. This change also allows for the possibility of having multiple roles/types for one variable. #221
All steps gain an id
field that will be used in the future to reference other steps.
The retain
option to prep
is now defaulted to TRUE
. If verbose = TRUE
, the approximate size of the data set is printed. #207
step_integer
converts data to ordered integers similar to LabelEncoder
#123 and #185step_geodist
can be used to calculate the distance between geocodes and a single reference location.step_arrange
, step_filter
, step_mutate
, step_sample
, and step_slice
implement their dplyr
analogs.step_nnmf
computes the non-negative matrix factorization for data.rsample
function prepper
was moved to recipes
(issue).step_step_string2factor
will now accept factors and leave them as-is.step_knnimpute
now excludes missing data in the variable to be imputed from the nearest-neighbor calculation. This would have resulted in some missing data to not be imputed (i.e. return another missing value).step_dummy
now produces a warning (instead of failing) when non-factor columns are selected. Only factor columns are used; no conversion is done for character data. issue #186dummy_names
gained a separator argument. issue #183step_downsample
and step_upsample
now have seed
arguments for more control over randomness.broom
is no longer used to get the tidy
generic. These are now contained in the generics
package.recipes
0.1.3check_range
breaks bake
if variable range in new data is outside the range that was learned from the train set (contributed by Edwin Thoen)
step_lag
can lag variables in the data set (contributed by Alex Hayes).
step_naomit
removes rows with missing data for specific columns (contributed by Alex Hayes).
step_rollimpute
can be used to impute data in a sequence or series by estimating their values within a moving window.
step_pls
can conduct supervised feature extraction for predictors.
step_log
gained an offset
argument.
step_log
gained a signed
argument (contributed by Edwin Thoen).
The internal functions sel2char
and printer
have been exported to enable other packages to contain steps.
When training new steps after some steps have been previously trained, the retain = TRUE
option should be set on previous invocations of prep
.
For step_dummy
:
one_hot = TRUE
option. Thanks to Davis Vaughan.contrast
option was removed. The step uses the global option for contrasts.step_other
will now convert novel levels of the factor to the "other" level.
step_bin2factor
now has an option to choose how the values are translated to the levels (contributed by Michael Levy).
bake
and juice
can now export basic data frames.
The okc
data were updated with two additional columns.
issue 125 that prevented several steps from working with dplyr grouped data frames. (contributed by Jeffrey Arnold)
issue 127 where options to step_discretize
were not being passed to discretize
.
recipes
0.1.2Edwin Thoen suggested adding validation checks for certain data characteristics. This fed into the existing notion of expanding recipes
beyond steps (see the non-step steps project). A new set of operations, called checks
, can now be used. These should throw an informative error when the check conditions are not met and return the existing data otherwise.
Steps now have a skip
option that will not apply preprocessing when bake
is used. See the article on skipping steps for more information.
check_missing
will validate that none of the specified variables contain missing data.
detect_step
can be used to check if a recipe contains a particular preprocessing operation.
step_num2factor
can be used to convert numeric data (especially integers) to factors.
step_novel
adds a new factor level to nominal variables that will be used when new data contain a level that did not exist when the recipe was prepared.
step_profile
can be used to generate design matrix grids for prediction profile plots of additive models where one variable is varied over a grid and all of the others are fixed at a single value.
step_downsample
and step_upsample
can be used to change the number of rows in the data based on the frequency distributions of a factor variable in the training set. By default, this operation is only applied to the training set; bake
ignores this operation.
step_naomit
drops rows when specified columns contain NA
, similar to tidyr::drop_na
.
step_lag
allows for the creation of lagged predictor columns.
step_spatialsign
now has the option of removing missing data prior to computing the norm.recipes
0.1.1bake
was changed from all_predictors()
to everything()
.verbose
option for prep
is now defaulted to FALSE
step_dummy
was fixed that makes sure that the correct binary variables are generated despite the levels or values of the incoming factor. Also, step_dummy
now requires factor inputs.step_dummy
also has a new default naming function that works better for factors. However, there is an extra argument (ordinal
) now to the functions that can be passed to step_dummy
.step_interact
now allows for selectors (e.g. all_predictors()
or starts_with("prefix")
to be used in the interaction formula.step_YeoJohnson
gained an na.rm
option.dplyr::one_of
was added to the list of selectors.step_bs
adds B-spline basis functions.step_unorder
converts ordered factors to unordered factors.step_count
counts the number of instances that a pattern exists in a string.step_string2factor
and step_factor2string
can be used to move between encodings.step_lowerimpute
is for numeric data where the values cannot be measured below a specific value. For these cases, random uniform values are used for the truncated values.step_zv
).tidy
methods were added for recipes and many (but not all) steps.bake.recipe
, the argument newdata
is now without a default.bake
and juice
can now save the final processed data set in sparse format. Note that, as the steps are processed, a non-sparse data frame is used to store the results.recipes
0.1.0First CRAN release.
prepare
to prep
per issue #59recipes
0.0.1.9003learn
has become prepare
and process
has become bake
recipes
0.0.1.9002step_lincomb
removes variables involved in linear combinations to resolve them.step_bin2factor
)step_regex
applies a regular expression to a character or factor vector to create dummy variables.step_dummy
and step_interact
do a better job of respecting missing values in the data set.recipes
0.0.1.9001recipe
objects was changed so that pipes can be used to create the recipe with a formula.process.recipe
lost the role
argument in factor of a general set of selectors. If no selector is used, all the predictors are returned.