recipes 0.1.2

General Changes:

• Edwin 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.

New Operations:

• check_missing will validate that none of the specified variables contain missing data.
• 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.

Other Changes:

• step_spatialsign now has the option of removing missing data prior to computing the norm.

recipes 0.1.1

• The default selectors for bake was changed from all_predictors() to everything().
• The verbose option for prep is now defaulted to FALSE
• A bug in 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.
  
• A step to remove simple zero-variance variables was added (step_zv).
• A series of tidy methods were added for recipes and many (but not all) steps.
• In 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.
• A formula method was added for recipes to get a formula with the outcome(s) and predictors based on the trained recipe.

recipes 0.1.0

First CRAN release.

• Changed prepare to prep per issue #59

recipes 0.0.1.9003

• Two of the main functions changed names. learn has become prepare and process has become bake

recipes 0.0.1.9002

New steps:

• step_lincomb removes variables involved in linear combinations to resolve them.
• A step for converting binary variables to factors (step_bin2factor)
• step_regex applies a regular expression to a character or factor vector to create dummy variables.

Other changes:

• step_dummy and step_interact do a better job of respecting missing values in the data set.

recipes 0.0.1.9001

• The class system for recipe 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.
• Two steps for simple imputation using the mean or mode were added.