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@amrit110
amrit110 committed Nov 24, 2023
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4 changes: 2 additions & 2 deletions 404.html
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<meta name="generator" content="Docusaurus v3.0.0">
<title data-rh="true">Page Not Found | CyclOps</title><meta data-rh="true" name="viewport" content="width=device-width,initial-scale=1"><meta data-rh="true" name="twitter:card" content="summary_large_image"><meta data-rh="true" property="og:url" content="https://vectorinstitute.github.io/cyclops/404.html"><meta data-rh="true" property="og:locale" content="en"><meta data-rh="true" name="docusaurus_locale" content="en"><meta data-rh="true" name="docusaurus_tag" content="default"><meta data-rh="true" name="docsearch:language" content="en"><meta data-rh="true" name="docsearch:docusaurus_tag" content="default"><meta data-rh="true" property="og:title" content="Page Not Found | CyclOps"><link data-rh="true" rel="icon" href="/cyclops/img/favicon.ico"><link data-rh="true" rel="canonical" href="https://vectorinstitute.github.io/cyclops/404.html"><link data-rh="true" rel="alternate" href="https://vectorinstitute.github.io/cyclops/404.html" hreflang="en"><link data-rh="true" rel="alternate" href="https://vectorinstitute.github.io/cyclops/404.html" hreflang="x-default"><link rel="alternate" type="application/rss+xml" href="/cyclops/blog/rss.xml" title="CyclOps RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/cyclops/blog/atom.xml" title="CyclOps Atom Feed"><link rel="stylesheet" href="/cyclops/assets/css/styles.bd9f4b2a.css">
<script src="/cyclops/assets/js/runtime~main.f74ffbd7.js" defer="defer"></script>
<script src="/cyclops/assets/js/main.de3a9079.js" defer="defer"></script>
<script src="/cyclops/assets/js/runtime~main.49642ce9.js" defer="defer"></script>
<script src="/cyclops/assets/js/main.8bc6fff8.js" defer="defer"></script>
</head>
<body class="navigation-with-keyboard">
<script>!function(){function t(t){document.documentElement.setAttribute("data-theme",t)}var e=function(){try{return new URLSearchParams(window.location.search).get("docusaurus-theme")}catch(t){}}()||function(){try{return localStorage.getItem("theme")}catch(t){}}();t(null!==e?e:"light")}(),function(){try{const c=new URLSearchParams(window.location.search).entries();for(var[t,e]of c)if(t.startsWith("docusaurus-data-")){var a=t.replace("docusaurus-data-","data-");document.documentElement.setAttribute(a,e)}}catch(t){}}()</script><div id="__docusaurus"><div role="region" aria-label="Skip to main content"><a class="skipToContent_fXgn" href="#__docusaurus_skipToContent_fallback">Skip to main content</a></div><nav aria-label="Main" class="navbar navbar--fixed-top"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Toggle navigation bar" aria-expanded="false" class="navbar__toggle clean-btn" type="button"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/cyclops/"><div class="navbar__logo"><img src="/cyclops/img/cyclops_logo-dark.png" alt="CyclOps Logo" class="themedComponent_mlkZ themedComponent--light_NVdE"><img src="/cyclops/img/cyclops_logo-dark.png" alt="CyclOps Logo" class="themedComponent_mlkZ themedComponent--dark_xIcU"></div><b class="navbar__title text--truncate"></b></a><a href="https://vectorinstitute.github.io/cyclops/api" target="_self" rel="noopener noreferrer" class="navbar__item navbar__link">API</a><a href="https://vectorinstitute.github.io/cyclops/api/tutorials" target="_self" rel="noopener noreferrer" class="navbar__item navbar__link">Tutorial</a></div><div class="navbar__items navbar__items--right"><a href="https://github.com/VectorInstitute/cyclops" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_nPIU"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></a><div class="navbarSearchContainer_Bca1"></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div id="__docusaurus_skipToContent_fallback" class="main-wrapper mainWrapper_z2l0"><main class="container margin-vert--xl"><div class="row"><div class="col col--6 col--offset-3"><h1 class="hero__title">Page Not Found</h1><p>We could not find what you were looking for.</p><p>Please contact the owner of the site that linked you to the original URL and let them know their link is broken.</p></div></div></main></div><footer class="footer footer--dark"><div class="container container-fluid"><div class="row footer__links"><div class="col footer__col"><div class="footer__title">Docs</div><ul class="footer__items clean-list"><li class="footer__item"><a href="https://vectorinstitute.github.io/cyclops/api" target="_self" rel="noopener noreferrer" class="footer__link-item">API</a></li><li class="footer__item"><a href="https://vectorinstitute.github.io/cyclops/api/tutorials" target="_self" rel="noopener noreferrer" class="footer__link-item">Tutorial</a></li></ul></div><div class="col footer__col"><div class="footer__title">More</div><ul class="footer__items clean-list"><li class="footer__item"><a class="footer__link-item" href="/cyclops/blog">Blog</a></li><li class="footer__item"><a href="https://github.com/VectorInstitute/cyclops" target="_blank" rel="noopener noreferrer" class="footer__link-item">GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_nPIU"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></a></li></ul></div></div><div class="footer__bottom text--center"><div class="footer__copyright">Copyright © 2023 CyclOps, built by AI Engineering @ Vector Institute</div></div></div></footer></div>
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48 changes: 5 additions & 43 deletions api/_sources/tutorials/kaggle/heart_failure_prediction.ipynb.txt
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"shutil.copy(f\"{report_path}\", \".\")\n",
"for i in range(4):\n",
" report._model_card.overview = None\n",
" report._model_card.quantitative_analysis = None\n",
" results_flat = flatten_results_dict(\n",
" results=results,\n",
" remove_metrics=[\"BinaryROCCurve\", \"BinaryPrecisionRecallCurve\"],\n",
" model_name=model_name,\n",
" )\n",
"\n",
" for name, metric in results_female_flat.items():\n",
" split, name = name.split(\"/\") # noqa: PLW2901\n",
" descriptions = {\n",
" \"BinaryPrecision\": \"The proportion of predicted positive instances that are correctly predicted.\",\n",
" \"BinaryRecall\": \"The proportion of actual positive instances that are correctly predicted. Also known as recall or true positive rate.\",\n",
" \"BinaryAccuracy\": \"The proportion of all instances that are correctly predicted.\",\n",
" \"BinaryAUROC\": \"The area under the receiver operating characteristic curve (AUROC) is a measure of the performance of a binary classification model.\",\n",
" \"BinaryF1Score\": \"The harmonic mean of precision and recall.\",\n",
" }\n",
" report.log_quantitative_analysis(\n",
" \"performance\",\n",
" name=name,\n",
" value=np.clip(metric + np.random.normal(0, 0.1), 0, 1),\n",
" description=descriptions[name],\n",
" metric_slice=split,\n",
" pass_fail_thresholds=0.7,\n",
" pass_fail_threshold_fns=lambda x, threshold: bool(x >= threshold),\n",
" )\n",
"\n",
" for name, metric in results_flat.items():\n",
" split, name = name.split(\"/\") # noqa: PLW2901\n",
" descriptions = {\n",
" \"BinaryPrecision\": \"The proportion of predicted positive instances that are correctly predicted.\",\n",
" \"BinaryRecall\": \"The proportion of actual positive instances that are correctly predicted. Also known as recall or true positive rate.\",\n",
" \"BinaryAccuracy\": \"The proportion of all instances that are correctly predicted.\",\n",
" \"BinaryAUROC\": \"The area under the receiver operating characteristic curve (AUROC) is a measure of the performance of a binary classification model.\",\n",
" \"BinaryF1Score\": \"The harmonic mean of precision and recall.\",\n",
" }\n",
" report.log_quantitative_analysis(\n",
" \"performance\",\n",
" name=name,\n",
" value=np.clip(metric + np.random.normal(0, 0.1), 0, 1),\n",
" description=descriptions[name],\n",
" metric_slice=split,\n",
" pass_fail_thresholds=0.7,\n",
" pass_fail_threshold_fns=lambda x, threshold: bool(x >= threshold),\n",
" for metric in report._model_card.quantitative_analysis.performance_metrics:\n",
" metric.value = np.clip(\n",
" metric.value + np.random.normal(0, 0.1),\n",
" 0,\n",
" 1,\n",
" )\n",
" report_path = report.export(\n",
" output_filename=\"heart_failure_report_periodic.html\",\n",
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2 changes: 1 addition & 1 deletion api/searchindex.js
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