{"id":23134407,"url":"https://github.com/danhalligan/islrv2-solutions-template","last_synced_at":"2025-05-07T13:34:43.477Z","repository":{"id":92111835,"uuid":"550143845","full_name":"danhalligan/ISLRv2-solutions-template","owner":"danhalligan","description":"A bookdown template for solutions to Introduction to Statistical Learning second edition","archived":false,"fork":false,"pushed_at":"2022-10-13T18:04:42.000Z","size":492,"stargazers_count":6,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-31T10:38:25.555Z","etag":null,"topics":["bookdown","islr","statistical-learning","template"],"latest_commit_sha":null,"homepage":"","language":"CSS","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/danhalligan.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-10-12T09:18:09.000Z","updated_at":"2025-01-23T05:11:33.000Z","dependencies_parsed_at":null,"dependency_job_id":"f56355af-ba44-4e4a-b69d-9fb8708a09be","html_url":"https://github.com/danhalligan/ISLRv2-solutions-template","commit_stats":null,"previous_names":[],"tags_count":0,"template":true,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danhalligan%2FISLRv2-solutions-template","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danhalligan%2FISLRv2-solutions-template/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danhalligan%2FISLRv2-solutions-template/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danhalligan%2FISLRv2-solutions-template/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/danhalligan","download_url":"https://codeload.github.com/danhalligan/ISLRv2-solutions-template/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252887488,"owners_count":21819908,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bookdown","islr","statistical-learning","template"],"created_at":"2024-12-17T12:10:19.978Z","updated_at":"2025-05-07T13:34:43.458Z","avatar_url":"https://github.com/danhalligan.png","language":"CSS","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ISLRv2 solutions template\n\nThis repository provides a [bookdown] [GitHub template] for completing the end\nof chapter \"Conceptual\" and \"Applied\" exercises from the the book [An\nIntroduction to Statistical Learning] by Gareth James, Daniela Witten, Trevor\nHastie and Robert Tibshirani.\n\n![ISLR cover](images/isl_small.jpg)\n\n## tl;dr\n\n* [Generate a new repository from this template].\n* Fill in your answers in [R Markdown] between the commented questions.\n* Push your edits to build your [bookdown book of solutions].\n\n[Generate a new repository from this template]: https://docs.github.com/en/repositories/creating-and-managing-repositories/creating-a-repository-from-a-template\n[bookdown book of solutions]: https://danhalligan.github.io/ISLRv2-solutions-template/\n\n## Usage\n\nTo complete your solutions, please [generate a new repository] from this\n template this repository first. You can then add solutions between the relevant\ncommented questions using [R markdown].\n\nAll questions from the original book have been translated to markdown and are\nquoted. You should provide your answers between the commented sections. \nFor example:\n\n\n```markdown\n\u003e For each of parts (a) through (d), indicate whether we would generally expect\n\u003e the performance of a flexible statistical learning method to be better or\n\u003e worse than an inflexible method. Justify your answer.\n\u003e\n\u003e a. The sample size n is extremely large, and the number of predictors p is\n\u003e    small.\n\nIn this case, a flexible method would be better because we have a large number\nof observations so can more reliably detect subtle patterns in the data and are\nlikely to avoid overfitting due to the low number of predictors.\n\n\u003e b. The number of predictors p is extremely large, and the number of\n\u003e    observations n is small.\n\nErm, perhaps the opposite?\n```\n\nYou may want to edit this `README.md` (to reflect that your version is not a\ntemplate!), and edit the `edit` tag in `_output.yml` to point to your\nrepository.\n\n## Data sets\n\nFor some questions, you are required to read in data. These data are provided\nin subdirectory `data`, downloaded from the [resources] section of \n\u003chttps://www.statlearning.com\u003e.\n\n\n## Implementation details\n\nThis repository is setup using bookdown and can build a [gitbook] style bookdown\nbook. Options are controlled in `_bookdown.yml` and `_output.yml`. Notably, I've\nset `new_session: yes` to start a new R session for each chapter of the book,\nso R packages required for answers should be reloaded for each chapter\nthat requires them.\n\nTo build the book locally you can run:\n\n```{r}\nbookdown::render_book('index.Rmd', 'bookdown::gitbook')\n```\n\nOr hit the \"build\" button in your RStudio session.\n\n### GitHub workflow\n\nI have specified a `.github/workflows` directory to implement a [GitHub\nworkflow] to build the book on updates to the repository and then host the \nbuilt book from GitHub pages. For example, to see the built version of this \ntemplate, see the [GitHub pages deployment]. When generating a new repository\nfrom this template you may need to enable workflows to get this to run. The \nworkflow will create a new branch `gh-pages` containing the built book and will\ndeploy this book for you.\n\n### Dependencies\n\nR package dependencies should be specified in the (fake) package `DESCRIPTION`\nfile. These dependencies will then be installed by the workflow so that your \nbook build works as expected.\n\n### Styling\n\nI've added some (minimal) styling for the book inside `islrv2.css`, notably,\nusing [Computer Modern] in homage to the the book (and the rest of this font's\nhistory!). To achieve this, I've made use of a [web version] of computer modern.\n\n## Final words\n\nMany thanks for the original authors for a great book on statistical learning.\n\nIf you notice any errors, feel free to make a pull request.\n\n[bookdown]: https://bookdown.org/\n[R Markdown]: https://rmarkdown.rstudio.com/\n[GitHub template]: https://github.blog/2019-06-06-generate-new-repositories-with-repository-templates/\n[An Introduction to Statistical Learning]: https://www.statlearning.com/\n[generate a new repository]: https://docs.github.com/en/repositories/creating-and-managing-repositories/creating-a-repository-from-a-template\n[resources]: https://www.statlearning.com/resources-second-edition\n[gitbook]: https://www.gitbook.com/\n[GitHub workflow]: https://docs.github.com/en/actions/using-workflows\n[GitHub pages deployment]: https://danhalligan.github.io/ISLRv2-solutions-template/\n[Computer Modern]: https://en.wikipedia.org/wiki/Computer_Modern\n[web version]: https://github.com/aaaakshat/cm-web-fonts\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdanhalligan%2Fislrv2-solutions-template","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdanhalligan%2Fislrv2-solutions-template","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdanhalligan%2Fislrv2-solutions-template/lists"}