{"id":838,"date":"2023-07-28T14:11:10","date_gmt":"2023-07-28T14:11:10","guid":{"rendered":"https:\/\/statorials.org\/pl\/python-podobienstwa-jaccarda\/"},"modified":"2023-07-28T14:11:10","modified_gmt":"2023-07-28T14:11:10","slug":"python-podobienstwa-jaccarda","status":"publish","type":"post","link":"https:\/\/statorials.org\/pl\/python-podobienstwa-jaccarda\/","title":{"rendered":"Jak obliczy\u0107 podobie\u0144stwo jaccarda w pythonie"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/pl\/podobienstwo-do-jacarda\/\" target=\"_blank\" rel=\"noopener\">Indeks podobie\u0144stwa Jaccarda<\/a> mierzy podobie\u0144stwo mi\u0119dzy dwoma zbiorami danych. Mo\u017ce wynosi\u0107 od 0 do 1. Im wy\u017csza liczba, tym bardziej podobne s\u0105 dwa zestawy danych.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Wska\u017anik podobie\u0144stwa Jaccarda oblicza si\u0119 w nast\u0119puj\u0105cy spos\u00f3b:<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>Podobie\u0144stwo Jaccarda<\/strong> = (liczba obserwacji w obu zbiorach) \/ (liczba w ka\u017cdym zbiorze)<\/span><\/p>\n<p> <span style=\"color: #000000;\">Lub zapisane w formie notacji:<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>J(A, B) =<\/strong> |A\u2229B| \/ |A\u222aB|<\/span><\/p>\n<p> <span style=\"color: #000000;\">W tym samouczku wyja\u015bniono, jak obliczy\u0107 podobie\u0144stwo Jaccarda dla dw\u00f3ch zbior\u00f3w danych w Pythonie.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Przyk\u0142ad: podobie\u0144stwo Jaccarda w Pythonie<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Za\u0142\u00f3\u017cmy, \u017ce mamy nast\u0119puj\u0105ce dwa zestawy danych:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> numpy <span style=\"color: #107d3f;\">as<\/span> np\n\na = [0, 1, 2, 5, 6, 8, 9]\nb = [0, 2, 3, 4, 5, 7, 9]<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Mo\u017cemy zdefiniowa\u0107 nast\u0119puj\u0105c\u0105 funkcj\u0119, aby obliczy\u0107 podobie\u0144stwo Jaccarda mi\u0119dzy dwoma zbiorami:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define Jaccard Similarity function<\/span>\n<span style=\"color: #107d3f;\">def<\/span> jaccard(list1, list2):\n    intersection = len(list(set(list1).intersection(list2)))\n    union = (len(list1) + len(list2)) - intersection\n    <span style=\"color: #107d3f;\">return<\/span> float(intersection) \/ union\n\n<span style=\"color: #008080;\">#find Jaccard Similarity between the two sets<\/span> \njaccard(a, b)\n\n0.4<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Podobie\u0144stwo Jaccarda mi\u0119dzy tymi dwiema listami wynosi <strong>0,4<\/strong> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">Zauwa\u017c, \u017ce funkcja zwr\u00f3ci <strong>0<\/strong> , je\u015bli oba zbiory nie maj\u0105 wsp\u00f3lnych warto\u015bci:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>c = [0, 1, 2, 3, 4, 5]\nd = [6, 7, 8, 9, 10]\n\njaccard(c, d)\n\n0.0<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Funkcja zwr\u00f3ci <strong>1<\/strong> , je\u015bli dwa zbiory s\u0105 identyczne:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>e = [0, 1, 2, 3, 4, 5]\nf = [0, 1, 2, 3, 4, 5]\n\njaccard(e, f)\n\n1.0<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Funkcja dzia\u0142a r\u00f3wnie\u017c dla zestaw\u00f3w zawieraj\u0105cych ci\u0105gi znak\u00f3w:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>g = ['cat', 'dog', 'hippo', 'monkey']\nh = ['monkey', 'rhino', 'ostrich', 'salmon']\n\njaccard(g, h)\n\n0.142857<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Mo\u017cesz tak\u017ce u\u017cy\u0107 tej funkcji, aby znale\u017a\u0107 <strong>odleg\u0142o\u015b\u0107 Jaccarda<\/strong> mi\u0119dzy dwoma zbiorami, kt\u00f3ra jest <em>odmienno\u015bci\u0105<\/em> mi\u0119dzy dwoma zbiorami i jest obliczana jako 1 \u2013 podobie\u0144stwo Jaccarda.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>a = [0, 1, 2, 5, 6, 8, 9]\nb = [0, 2, 3, 4, 5, 7, 9]\n\n<span style=\"color: #008080;\">#find Jaccard distance between sets <em>a<\/em> and <em>b<\/em><\/span>\n1 - jaccard(a, b)\n\n0.6<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>Powi\u0105zane:<\/strong> <a href=\"https:\/\/statorials.org\/pl\/podobienstwo-jacarda-w-r\/\" target=\"_blank\" rel=\"noopener noreferrer\">Jak obliczy\u0107 podobie\u0144stwo Jaccarda w R<\/a><\/span><\/p>\n<p> <em><span style=\"color: #000000;\">Wi\u0119cej informacji na temat indeksu podobie\u0144stwa Jaccarda mo\u017cna znale\u017a\u0107 na <a href=\"https:\/\/en.wikipedia.org\/wiki\/Jaccard_index\" target=\"_blank\" rel=\"noopener noreferrer\">tej stronie Wikipedii<\/a> .<\/span><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Indeks podobie\u0144stwa Jaccarda mierzy podobie\u0144stwo mi\u0119dzy dwoma zbiorami danych. Mo\u017ce wynosi\u0107 od 0 do 1. Im wy\u017csza liczba, tym bardziej podobne s\u0105 dwa zestawy danych. Wska\u017anik podobie\u0144stwa Jaccarda oblicza si\u0119 w nast\u0119puj\u0105cy spos\u00f3b: Podobie\u0144stwo Jaccarda = (liczba obserwacji w obu zbiorach) \/ (liczba w ka\u017cdym zbiorze) Lub zapisane w formie notacji: J(A, B) = |A\u2229B| [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"class_list":["post-838","post","type-post","status-publish","format-standard","hentry","category-przewodnik"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Jak obliczy\u0107 podobie\u0144stwo Jaccarda w Pythonie - Statorials<\/title>\n<meta name=\"description\" content=\"Proste wyja\u015bnienie, jak obliczy\u0107 podobie\u0144stwo Jaccarda mi\u0119dzy dwoma zbiorami danych w Pythonie.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/pl\/python-podobienstwa-jaccarda\/\" \/>\n<meta property=\"og:locale\" content=\"pl_PL\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Jak obliczy\u0107 podobie\u0144stwo Jaccarda w Pythonie - Statorials\" \/>\n<meta property=\"og:description\" content=\"Proste wyja\u015bnienie, jak obliczy\u0107 podobie\u0144stwo Jaccarda mi\u0119dzy dwoma zbiorami danych w Pythonie.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/pl\/python-podobienstwa-jaccarda\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-28T14:11:10+00:00\" \/>\n<meta name=\"author\" content=\"Benjamin Anderson\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Napisane przez\" \/>\n\t<meta name=\"twitter:data1\" content=\"Benjamin Anderson\" \/>\n\t<meta name=\"twitter:label2\" content=\"Szacowany czas czytania\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minuty\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/pl\/python-podobienstwa-jaccarda\/\",\"url\":\"https:\/\/statorials.org\/pl\/python-podobienstwa-jaccarda\/\",\"name\":\"Jak obliczy\u0107 podobie\u0144stwo Jaccarda w Pythonie - Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/pl\/#website\"},\"datePublished\":\"2023-07-28T14:11:10+00:00\",\"dateModified\":\"2023-07-28T14:11:10+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/pl\/#\/schema\/person\/6484727a4612df3e69f016c3129c6965\"},\"description\":\"Proste wyja\u015bnienie, jak obliczy\u0107 podobie\u0144stwo Jaccarda mi\u0119dzy dwoma zbiorami danych w Pythonie.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/pl\/python-podobienstwa-jaccarda\/#breadcrumb\"},\"inLanguage\":\"pl-PL\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/pl\/python-podobienstwa-jaccarda\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/pl\/python-podobienstwa-jaccarda\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Dom\",\"item\":\"https:\/\/statorials.org\/pl\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Jak obliczy\u0107 podobie\u0144stwo jaccarda w pythonie\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/pl\/#website\",\"url\":\"https:\/\/statorials.org\/pl\/\",\"name\":\"Statorials\",\"description\":\"Tw\u00f3j przewodnik po kompetencjach statystycznych!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/pl\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"pl-PL\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/pl\/#\/schema\/person\/6484727a4612df3e69f016c3129c6965\",\"name\":\"Benjamin Anderson\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"pl-PL\",\"@id\":\"https:\/\/statorials.org\/pl\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/statorials.org\/pl\/wp-content\/uploads\/2023\/11\/Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"https:\/\/statorials.org\/pl\/wp-content\/uploads\/2023\/11\/Benjamin-Anderson-96x96.jpg\",\"caption\":\"Benjamin Anderson\"},\"description\":\"Cze\u015b\u0107, jestem Benjamin i jestem emerytowanym profesorem statystyki, kt\u00f3ry zosta\u0142 oddanym nauczycielem Statorials. 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