Add engine specification field for predictor encodings #319
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Merge branch 'master' into encoding-options # Conflicts: # R/linear_reg_data.R # R/svm_poly_data.R # R/svm_rbf_data.R # tests/testthat/test_svm_poly.R # tests/testthat/test_svm_rbf.R
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This PR also fixes the function used with Spark decision trees 🌳 for regression. |
topepo
reviewed
May 26, 2020
This was referenced Jun 2, 2020
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This pull request has been automatically locked. If you believe you have found a related problem, please file a new issue (with a reprex: https://reprex.tidyverse.org) and link to this issue. |
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Closes #290.
This PR adds the field for engine-specific encodings (only dummy/indicator variables for now).
For example, the encoding options for ranger are:
While the encoding options for vanilla logistic regression are:
These changes depend on handling the names for data arguments implemented in #315 and #316.
These encodings can be used in workflows so that the user experiences the same behavior around dummy variable creation in both parsnip and workflows.
I am pretty confident that
predictor_indicators = TRUE / FALSEis correct for all the model + engine combinations except for liquidSVM. I was having trouble getting output from those models and could use some double-checking.