usethis::use_zip(url="https://dicook.github.io/mulgar_book/code_and_data.zip")Appendix C — Links to Book Code and Additional Data
The code and data and an RStudio project can be downloaded with
Alternatively, individual files can be downloaded from the links below.
C.1 Additional data
Table C.1 lists additional data available on the book web site at https://dicook.github.io/mulgar_book/data.
| Description | Link |
|---|---|
| Saved 2D tour path for the aflw data | <a href='https://dicook.github.io/mulgar_book/data/aflw_pct.rda'> aflw_pct.rda </a> |
| Saved clusters of the penguins data from detourr | <a href='https://dicook.github.io/mulgar_book/data/detourr_penguins.csv'> detourr_penguins.csv </a> |
| Saved clusters of the fake trees data from detourr | <a href='https://dicook.github.io/mulgar_book/data/fake_trees_sb.csv'> fake_trees_sb.csv </a> |
| Tidied penguins data | <a href='https://dicook.github.io/mulgar_book/data/penguins_sub.rda'> penguins_sub.rda </a> |
| Saved 2D tour path for penguins data | <a href='https://dicook.github.io/mulgar_book/data/penguins_tour_path.rda'> penguins_tour_path.rda </a> |
| risk survey | <a href='https://dicook.github.io/mulgar_book/data/risk_MSA.rds'> risk_MSA.rds </a> |
| penguins NN model | <a href='https://dicook.github.io/mulgar_book/data/penguins_cnn> penguins_cnn </a> |
| fashion MNST NN model | <a href='https://dicook.github.io/mulgar_book/data/fashion_cnn> fashion_cnn </a> |
| penguins SHAP values | <a href='https://dicook.github.io/mulgar_book/data/p_exp_sv.rda> p_exp_sv.rda </a> |
C.2 Code files
Table C.2 lists additional data available on the book web site at https://dicook.github.io/mulgar_book/code.
| Chapter | Link | Filename |
|---|---|---|
| 1 Picturing high dimensions | 1-intro.R | 1-intro.R |
| 2 Notation conventions and R objects | 2-notation.R | 2-notation.R |
| 3 Overview of dimension reduction | 3-overview-dimred.R | 3-overview-dimred.R |
| 4 Principal component analysis | 4-pca.R | 4-pca.R |
| 5 Non-linear dimension reduction | 5-nldr.R | 5-nldr.R |
| 6 Overview of clustering | 6-overview-clust.R | 6-overview-clust.R |
| 7 Spin-and-brush approach | 7-spin-and-brush.R | 7-spin-and-brush.R |
| 8 Hierarchical clustering | 8-hierarchical.R | 8-hierarchical.R |
| 9 k-means clustering | 9-kmeans.R | 9-kmeans.R |
| 10 Model-based clustering | 10-model-based.R | 10-model-based.R |
| 11 Self-organizing maps | 11-som.R | 11-som.R |
| 12 Summarising and comparing clustering results | 12-summary-clust.R | 12-summary-clust.R |
| 13 Overview of supervised classification | 13-intro-class.R | 13-intro-class.R |
| 14 Linear discriminant analysis | 14-lda.R | 14-lda.R |
| 15 Trees and forests | 15-forests.R | 15-forests.R |
| 16 Support vector machines | 16-svm.R | 16-svm.R |
| 17 Neural networks and deep learning | 17-nn.R | 17-nn.R |
| 18 Exploring misclassifications | 18-summary-class.R | 18-summary-class.R |
| A Toolbox | A-toolbox.R | NA |
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