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hfrickjuliasilge
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Add an article with minimal examples (#527)
* add article with minimal examples for fitting and predicting * fix indentation * all examples indented to get collapsing right * make headers work within the collapsable section * add id tags so that we can link to specific sections * (failed) attempt to use the tag to link from help page to the article * change order * added links to pkgdown site in the help pages * let GA build the site and deploy * don't call it minimal because it's still quite a bit to take in * add intro sentence * add tensorflow for future examples * more examples `multinom_reg()`: nnet, keras `mlp()`: nnet, keras `mars()`: earth * suppress auto-linking in section headings * more examples `logistic_reg()`: glm, glmnet, keras, LiblineaR, stan `linear_reg()`: lm, glmnet, keras, stan `decision_tree()`: rpart, C5.0 `boost_tree()`: xgboost, C5.0 * remove `set_mode()` when the model only has one mode * added headings * include info on model/mode/engine Co-authored-by: Julia Silge <julia.silge@gmail.com> * Update vignettes/articles/template-cls-multi-class.R Co-authored-by: Julia Silge <julia.silge@gmail.com> Co-authored-by: Julia Silge <julia.silge@gmail.com>
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.github/workflows/pkgdown.yaml

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pak::pkg_install("C50")
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shell: Rscript {0}
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- name: Install Miniconda
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run: |
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Rscript -e "pak::pkg_install('rstudio/reticulate')"
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Rscript -e "reticulate::install_miniconda()"
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- name: Find Miniconda on macOS
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if: runner.os == 'macOS'
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run: echo "options(reticulate.conda_binary = reticulate:::miniconda_conda())" >> .Rprofile
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- name: Install TensorFlow
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run: |
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reticulate::conda_create('r-reticulate', packages = c('python==3.6.9'))
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tensorflow::install_tensorflow(version='1.14.0')
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shell: Rscript {0}
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- name: Install package
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run: R CMD INSTALL .
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_pkgdown.yml

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# https://github.com/tidyverse/tidytemplate for css
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development:
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mode: auto
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mode: release
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figures:
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href: https://www.tidymodels.org/learn/develop/models/
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- text: Evaluating submodels with the same model object
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href: articles/articles/Submodels.html
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- text: Fitting and Predicting with parsnip
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href: articles/articles/Examples.html
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- text: News
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href: news/index.html
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- text: Reference

man/details_multinom_reg_glmnet.Rd

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man/details_nearest_neighbor_kknn.Rd

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man/details_rand_forest_randomForest.Rd

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man/details_rand_forest_ranger.Rd

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man/details_svm_linear_LiblineaR.Rd

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man/details_svm_linear_kernlab.Rd

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man/details_svm_poly_kernlab.Rd

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man/details_svm_rbf_kernlab.Rd

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