{"id":990,"date":"2023-07-28T02:02:31","date_gmt":"2023-07-28T02:02:31","guid":{"rendered":"https:\/\/statorials.org\/it\/vero-pitone\/"},"modified":"2023-07-28T02:02:31","modified_gmt":"2023-07-28T02:02:31","slug":"vero-pitone","status":"publish","type":"post","link":"https:\/\/statorials.org\/it\/vero-pitone\/","title":{"rendered":"Come calcolare l&#39;rmse in python"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>L&#8217;errore quadratico medio (RMSE)<\/strong> \u00e8 una metrica che ci dice quanto distano, in media, i nostri valori previsti dai valori osservati in un modello. Viene calcolato come segue:<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>RMSE<\/strong> = \u221a[ \u03a3(P <sub>i<\/sub> \u2013 O <sub>i<\/sub> ) <sup>2<\/sup> \/ n ]<\/span><\/p>\n<p> <span style=\"color: #000000;\">Oro:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\u03a3 \u00e8 un simbolo di fantasia che significa &#8220;somma&#8221;<\/span><\/li>\n<li> <span style=\"color: #000000;\"><sub>Pi<\/sub> \u00e8 il valore previsto per l&#8217; <sup>i-esima<\/sup> osservazione<\/span><\/li>\n<li> <span style=\"color: #000000;\">O <sub>i<\/sub> \u00e8 il valore osservato per l&#8217; <sup>i-esima<\/sup> osservazione<\/span><\/li>\n<li> <span style=\"color: #000000;\">n \u00e8 la dimensione del campione<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">Questo tutorial spiega un metodo semplice per calcolare RMSE in Python.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Esempio: calcola RMSE in Python<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Supponiamo di avere le seguenti tabelle di valori effettivi e previsti:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>actual= [34, 37, 44, 47, 48, 48, 46, 43, 32, 27, 26, 24]\npred = [37, 40, 46, 44, 46, 50, 45, 44, 34, 30, 22, 23]\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Per calcolare l&#8217;RMSE tra i valori effettivi e quelli previsti, possiamo semplicemente prendere la radice quadrata della<\/span> funzione <a href=\"https:\/\/scikit-learn.org\/stable\/modules\/generated\/sklearn.metrics.mean_squared_error.html\" target=\"_blank\" rel=\"noopener noreferrer\">Mean_squared_error()<\/a> <span style=\"color: #000000;\">dalla libreria sklearn.metrics:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\"><span style=\"color: #008080;\">#import necessary libraries<\/span>\nfrom<\/span> sklearn.metrics <span style=\"color: #008000;\">import<\/span> mean_squared_error\n<span style=\"color: #008000;\">from<\/span> math <span style=\"color: #008000;\">import<\/span> sqrt\n\n<span style=\"color: #008080;\">#calculate RMSE\n<\/span>sqrt(mean_squared_error(actual, pred)) \n\n2.4324199198\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">L&#8217;RMSE risulta essere <strong>2.4324<\/strong> .<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Come interpretare l&#8217;RMSE<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">RMSE \u00e8 un modo utile per vedere quanto bene un modello \u00e8 in grado di adattarsi a un set di dati.<\/span> <span style=\"color: #000000;\">Maggiore \u00e8 l&#8217;RMSE, maggiore \u00e8 la differenza tra i valori previsti e quelli osservati, il che significa che peggiore \u00e8 l&#8217;adattamento del modello ai dati. Al contrario, pi\u00f9 piccolo \u00e8 l\u2019RMSE, migliore \u00e8 la capacit\u00e0 del modello di adattare i dati.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Pu\u00f2 essere particolarmente utile confrontare l&#8217;RMSE di due diversi modelli per vedere quale modello si adatta meglio ai dati.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Risorse addizionali<\/strong><\/span><\/h3>\n<p> <a href=\"https:\/\/statorials.org\/it\/calcolatrice-rmse\/\" target=\"_blank\" rel=\"noopener noreferrer\">Calcolatore RMSE<\/a><br \/> <a href=\"https:\/\/statorials.org\/it\/significa-errore-quadrato-python\/\" target=\"_blank\" rel=\"noopener noreferrer\">Come calcolare l&#8217;errore quadratico medio (MSE) in Python<\/a><br \/> <a href=\"https:\/\/statorials.org\/it\/carta-pitone\/\" target=\"_blank\" rel=\"noopener noreferrer\">Come calcolare MAPE in Python<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>L&#8217;errore quadratico medio (RMSE) \u00e8 una metrica che ci dice quanto distano, in media, i nostri valori previsti dai valori osservati in un modello. Viene calcolato come segue: RMSE = \u221a[ \u03a3(P i \u2013 O i ) 2 \/ n ] Oro: \u03a3 \u00e8 un simbolo di fantasia che significa &#8220;somma&#8221; Pi \u00e8 il valore [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Come calcolare RMSE in Python - Statorials<\/title>\n<meta name=\"description\" content=\"Una semplice spiegazione su come calcolare RMSE in Python.\" \/>\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\/it\/vero-pitone\/\" \/>\n<meta property=\"og:locale\" content=\"it_IT\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Come calcolare RMSE in Python - Statorials\" \/>\n<meta property=\"og:description\" content=\"Una semplice spiegazione su come calcolare RMSE in Python.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/it\/vero-pitone\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-28T02:02:31+00:00\" \/>\n<meta name=\"author\" content=\"Benjamin anderson\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Benjamin anderson\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minuto\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/it\/vero-pitone\/\",\"url\":\"https:\/\/statorials.org\/it\/vero-pitone\/\",\"name\":\"Come calcolare RMSE in Python - Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/it\/#website\"},\"datePublished\":\"2023-07-28T02:02:31+00:00\",\"dateModified\":\"2023-07-28T02:02:31+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/it\/#\/schema\/person\/0896f191fb9fb019f2cd8623112cb3ae\"},\"description\":\"Una semplice spiegazione su come calcolare RMSE in Python.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/it\/vero-pitone\/#breadcrumb\"},\"inLanguage\":\"it-IT\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/it\/vero-pitone\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/it\/vero-pitone\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Casa\",\"item\":\"https:\/\/statorials.org\/it\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Come calcolare l&#39;rmse in python\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/it\/#website\",\"url\":\"https:\/\/statorials.org\/it\/\",\"name\":\"Statorials\",\"description\":\"La tua guida all&#039;alfabetizzazione statistica!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/it\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"it-IT\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/it\/#\/schema\/person\/0896f191fb9fb019f2cd8623112cb3ae\",\"name\":\"Benjamin anderson\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"it-IT\",\"@id\":\"https:\/\/statorials.org\/it\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/statorials.org\/it\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"https:\/\/statorials.org\/it\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"caption\":\"Benjamin anderson\"},\"description\":\"Ciao, sono Benjamin, un professore di statistica in pensione diventato insegnante dedicato di Statorials. 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