_pkgdown.yml

url: http://www.schlosslab.org/mikropml
destination: docs
development:
  mode: auto
template:
  bootstrap: 5
articles:
- title: Paper
  navbar: Paper
  contents:
  - paper
- title: Vignettes
  navbar: Vignettes
  contents:
  - introduction
  - preprocess
  - tuning
  - parallel
authors:
    Begüm Topçuoğlu:
        href: "https://github.com/BTopcuoglu"
    Zena Lapp:
        href: "https://github.com/zenalapp"
    Kelly Sovacool:
        href: "https://github.com/kelly-sovacool"
    Patrick Schloss:
        href: "https://github.com/pschloss"

home:
  sidebar:
    structure: [links, license, community, citation, authors, dev, custom]
    components:
      custom:
        title: Impact metrics
        text: >
          &nbsp;<br>
          <script async src="https://badge.dimensions.ai/badge.js" charset="utf-8"></script>
          <script type='text/javascript' src='https://d1bxh8uas1mnw7.cloudfront.net/assets/embed.js'></script>
          <span class="__dimensions_badge_embed__" data-doi="10.21105/joss.03073" data-style="small_circle"></span>
          &nbsp;<br>
          <div data-badge-type="donut" data-doi="10.21105/joss.03073" data-condensed="true" data-badge-popover="right"  class="altmetric-embed"></div>

reference:
- title: Main
  desc: >
    The foundations for training machine learning models.
  contents:
  - mikropml
  - preprocess_data
  - run_ml
- title: Model evaluation
  desc: >
    Evaluate and interpret models.
  contents:
  - get_feature_importance
  - get_performance_tbl
  - sensspec
  - calc_mean_perf
  - calc_baseline_precision
  - calc_balanced_precision
  - compare_models
  - permute_p_value
  - bootstrap_performance
- title: Plotting helpers
  desc: >
    Visualize results to help you tune hyperparameters and choose model methods.
  contents:
  - starts_with('plot')
  - tidy_perf_data
  - get_hp_performance
  - combine_hp_performance
- title: Package Data
- subtitle: datasets
  contents:
  - otu_small
  - otu_mini_bin
  - otu_mini_multi
  - otu_mini_multi_group
  - otu_data_preproc
- subtitle: ML results
  contents:
  - contains("results")
- subtitle: misc
  contents:
  - otu_mini_cv
  - replace_spaces
- title: Pipeline customization
  desc: >
    Customize various steps of the pipeline beyond the arguments provided by
    run_ml() and preprocess_data().
  contents:
  - remove_singleton_columns
  - get_caret_processed_df
  - randomize_feature_order
  - get_partition_indices
  - get_outcome_type
  - get_hyperparams_list
  - get_tuning_grid
  - define_cv
  - get_perf_metric_name
  - get_perf_metric_fn
  - train_model
  - calc_perf_metrics
  - group_correlated_features