tidypredict 0.5

• Changes maintainer to Edgar Ruiz
• Updates author's email addresses
• Removes dependency with stringr
• Fixes issue with earth parsed_models (#108)
• Addresses issues with XGBoost models
• Improvements to XGBoosts tests

tidypredict 0.4.9

• Fixes issue handling GLM Binomial earth models (#97)

• Adds capability to handle single simple Cubist models (#57)

• Fixed parenthesis issue in the creation of the interval formula (#76)

• Fixed bug in SQL query generation for XGBoost models with objective binary:logistic.

• Re-licensed package from GPL-3 to MIT. See consent from copyright holders here.

tidypredict 0.4.8

• CRAN submission for a broken test case.

tidypredict 0.4.7

• Change to with with version 5.1.2 and above of the earth package. As a result, tidypredict will only parse objects created by this and later versions of earth.

tidypredict 0.4.6

• Small release for xgboost changes.

tidypredict 0.4.2

• Parses ranger classification models
• Adds method support for broom’s tidy() function. Regression models only
• Adds as_parsed_model() function. It adds the proper class components to the list.
• Adds initial support for partykit’s ctree() model
• Adds support for parsnip fitted models: lm, randomForest, ranger, and earth
• Adds support for xgb.Booster models provided by the xgboost package (@Athospd, #43)
• Adds support for Cubist::cubist() models (# 36)

tidypredict 0.3

New features

• Adds support for MARS models provided by the earth package

Improvements

• New parsed models are now list objects as opposed to data frames.

• tidypredict_to_column() no longer supports ranger and randomForest because of the multiple queries generated by multiple trees.

• All functions that read the parsed models and create the tidy eval formula now use the list object.

• Most of the code that depends on dplyr programming has been removed.

• Removes dependencies on: tidyr, tibble

Bug Fixes

• It now returns all of the trees instead of just one for tree based models (randomForest & ranger) (#29)

tidypredict 0.2.1

• Adds compatibility with the latest version of tibble

tidypredict 0.2.0

New features

• Add support for ranger() models.

Bug fixes

• Using x ~. in a randomForest() formula fails (#18 @washcycle).

tidypredict 0.1.0

It parses a fitted 'R' model object, and returns a formula in 'Tidy Eval' code that calculates the predictions.

It works with several databases back-ends because it leverages 'dplyr' and 'dbplyr' for the final 'SQL' translation of the algorithm. It currently supports lm(), glm() and randomForest() models.