{"id":34071,"date":"2022-02-25T10:06:00","date_gmt":"2022-02-25T09:06:00","guid":{"rendered":"http:\/\/54.194.80.134.nip.io\/blog\/napredna-analitika-s-r-pregled\/"},"modified":"2022-06-06T23:07:11","modified_gmt":"2022-06-06T21:07:11","slug":"napredna-analitika-s-r-pregled","status":"publish","type":"post","link":"https:\/\/www.cubeserv.com\/hr\/napredna-analitika-s-r-pregled\/","title":{"rendered":"Napredna analiza s R: Pregled"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"34071\" class=\"elementor elementor-34071 elementor-33228\" data-elementor-settings=\"{&quot;element_pack_global_tooltip_width&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;element_pack_global_tooltip_width_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;element_pack_global_tooltip_width_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;element_pack_global_tooltip_padding&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_padding_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_padding_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_border_radius&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_border_radius_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_border_radius_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true}}\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-b326c7b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"b326c7b\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-66 elementor-top-column elementor-element elementor-element-f5fc07e\" data-id=\"f5fc07e\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-feec4ec elementor-widget elementor-widget-text-editor\" data-id=\"feec4ec\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\tIako je programski jezik R prisutan od ranih 90-ih, dobio je veliku slavu i pozornost u prethodnom desetlje\u0107u, uglavnom zbog svog \u0161irokog raspona funkcionalnosti povezanih sa statisti\u010dkom analizom i znano\u0161\u0107u o podacima. Zna\u010dajan razlog je taj \u0161to ne zahtijeva \u010dvrstu programsku pozadinu da bi ga ljudi po\u010deli koristiti.\r\n\r\nNastavljaju\u0107i na\u0161u seriju analitike s R, danas \u0107emo istra\u017eiti naprednu analitiku s R. Uklju\u010dene su teme kao \u0161to su regresijska analiza s R-om i predvi\u0111anje vremenskih serija. Ako \u017eelite pogledati prethodni \u010dlanak na temelju po\u010detni\u010dke razine analytics, slobodno kliknite ovdje.\r\n\r\nDakle, krenimo bez daljnjeg.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-b39b05e\" data-id=\"b39b05e\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-50c00d2 elementor-widget elementor-widget-image\" data-id=\"50c00d2\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"768\" height=\"614\" src=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/4_BI-Management-768x614.jpg\" class=\"attachment-medium_large size-medium_large wp-image-33359\" alt=\"focussed Analytics\" srcset=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/4_BI-Management-768x614.jpg 768w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/4_BI-Management-300x240.jpg 300w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/4_BI-Management-1024x819.jpg 1024w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/4_BI-Management.jpg 1440w\" sizes=\"(max-width: 768px) 100vw, 768px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-809ac5b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"809ac5b\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-5ff39b2\" data-id=\"5ff39b2\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1d2198f elementor-widget elementor-widget-text-editor\" data-id=\"1d2198f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h2>Iscrtavanje dijagrama programskim jezikom R<\/h2>\r\nPo\u010dev\u0161i od osnova, pogledajmo sve razli\u010dite vrste dijagrama koje mo\u017eemo napraviti u R. Iako je crtanje grafova relativno jednostavan posao i moglo bi se re\u0107i da ne ispunjava uvjete za naprednu analitiku, bitno je poznavati razli\u010dite vrste dostupnih dijagrama i kad koji koristiti ovisno o scenariju. Rezultati koje mogu pru\u017eiti u nekoliko redaka koda ponekad su zna\u010dajniji od same napredne analitike.\r\n\r\n<strong>ggplot2 \u2013 Va\u0161 najbolji prijatelj!<\/strong>\r\n\r\nBez obzira kakve planove \u017eelite napraviti u R-u, ggplot2 bi uvijek trebao biti va\u0161 prvi izbor. To je daleko naj\u010de\u0161\u0107e kori\u0161teni paket od strane R-programera kada ne\u0161to planiraju.\r\n\r\nPogledajmo razli\u010dite parcele koje nudi paket ggplot2 i vidimo za koje su aplikacije prikladne. Za potrebe demonstracije koristit \u0107emo poznati skup podataka Iris.\r\n\r\nDakle, pokrenimo RStudio i krenimo s planiranjem!\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-eb8f891 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"eb8f891\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-946653f\" data-id=\"946653f\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c9016ab elementor-widget elementor-widget-code-highlight\" data-id=\"c9016ab\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"prismjs-default copy-to-clipboard \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-r \">\n\t\t\t\t<code readonly=\"true\" class=\"language-r\">\n\t\t\t\t\t<xmp>install.packages(\"tidyverse\")\r\nlibrary(datasets)\r\ndata(\"iris\")<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4992dae elementor-widget elementor-widget-spacer\" data-id=\"4992dae\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-006e81d elementor-widget elementor-widget-text-editor\" data-id=\"006e81d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h3>1. Stup\u010dasti dijagrami<\/h3>\r\nStup\u010dasti dijagrami su naj\u010de\u0161\u0107a vrsta grafova koji se koriste u analizi. Koriste se kad god \u017eelite usporediti vrijednosti razli\u010ditih kategorija pomo\u0107u okomitih traka koje predstavljaju vrijednosti. Ove \u0161ipke razli\u010dite visine \u010dine usporedbu vrlo prikladnom. <span style=\"font-weight: 400;\">Evo primjera koji prikazuje duljinu lapova razli\u010ditih vrsta.<\/span>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c124730 elementor-widget elementor-widget-code-highlight\" data-id=\"c124730\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"prismjs-default copy-to-clipboard \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-r \">\n\t\t\t\t<code readonly=\"true\" class=\"language-r\">\n\t\t\t\t\t<xmp>ggplot(data=iris, aes(x=Species, fill = Species)) + \r\ngeom_bar() + \r\n  xlab(\"Species\") +  \r\n  ylab(\"Count\") + \r\n  ggtitle(\"Bar plot of Sepal Length\")<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2ac32df elementor-widget elementor-widget-image\" data-id=\"2ac32df\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"862\" height=\"550\" src=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_Bar_Graphs.jpeg\" class=\"attachment-large size-large wp-image-33241\" alt=\"simple bar chart\" srcset=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_Bar_Graphs.jpeg 862w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_Bar_Graphs-300x191.jpeg 300w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_Bar_Graphs-768x490.jpeg 768w\" sizes=\"(max-width: 862px) 100vw, 862px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7641211 elementor-widget elementor-widget-spacer\" data-id=\"7641211\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e2223f7 elementor-widget elementor-widget-text-editor\" data-id=\"e2223f7\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h3>2. Histogrami<\/h3>\r\nHistogrami su vrlo sli\u010dni stup\u010dastim dijagramima. Koriste se za grafi\u010dki prikaz kontinuiranih podataka i grupiranje u spremnike. Svaka traka u histogramu ima vi\u0161e spremnika s razli\u010ditim bojama \u0161to olak\u0161ava uvid u frekvenciju svake pojedina\u010dne kategorije. Evo kako ih mo\u017eemo napraviti pomo\u0107u ggplot2.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-aff333e elementor-widget elementor-widget-code-highlight\" data-id=\"aff333e\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"prismjs-default copy-to-clipboard \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-javascript \">\n\t\t\t\t<code readonly=\"true\" class=\"language-javascript\">\n\t\t\t\t\t<xmp>ggplot(data=iris, aes(x=Sepal.Width)) + \r\n  geom_histogram(binwidth=0.2, color=\"black\", aes(fill=Species)) + \r\n  xlab(\"Sepal Width\") + \r\n  ylab(\"Frequency\") + \r\n  ggtitle(\"Histogram of Sepal Width\")<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d94d3a8 elementor-widget elementor-widget-image\" data-id=\"d94d3a8\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/elementor\/thumbs\/Rplot_Histogram-qeyihcsgodltmsowgtal57czt6hfvsjvotyepiu4n0.jpeg\" title=\"Rplot_Histogram\" alt=\"example Histogram\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-99bd835 elementor-widget elementor-widget-spacer\" data-id=\"99bd835\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-32bd43e elementor-widget elementor-widget-text-editor\" data-id=\"32bd43e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h3>3. Box Plots<\/h3>\r\nBox plot vizualizira cjelokupnu distribuciju podataka na vrlo kompaktan na\u010din. S jednim okvirom mo\u017eete vidjeti i gornji i donji \u010detvrt i sve prisutne vanjske vrijednosti, zajedno s rasponom \u0161irenja podataka.\r\n\r\nZanima vas kako \u010ditati box plot? Kliknite <a href=\"https:\/\/www.statisticshowto.com\/probability-and-statistics\/descriptive-statistics\/box-plot\/#:~:text=Back%20to%20Top-,How%20to%20Read%20a%20Box%20Plot,(the%2075%25%20mark).\">ovdje<\/a>.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ff2a9ad elementor-widget elementor-widget-code-highlight\" data-id=\"ff2a9ad\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"prismjs-default copy-to-clipboard \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-r \">\n\t\t\t\t<code readonly=\"true\" class=\"language-r\">\n\t\t\t\t\t<xmp>ggplot(data=iris, aes(x=Species, y=Sepal.Length)) +\r\n  geom_boxplot(aes(fill=Species)) + \r\n  ylab(\"Sepal Length\") + ggtitle(\"Iris Boxplot\")<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-704730a elementor-widget elementor-widget-image\" data-id=\"704730a\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/elementor\/thumbs\/Rplot_Boxplot-qeyiheo521oea0m65u3ua6vwzy86b6rcd39do2rcak.jpeg\" title=\"Rplot_Boxplot\" alt=\"example Box Plots\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cdff762 elementor-widget elementor-widget-spacer\" data-id=\"cdff762\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8ba700e elementor-widget elementor-widget-text-editor\" data-id=\"8ba700e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h3>4. Grafikon raspr\u0161enja<\/h3>\r\nPosljednje, ali ne i najmanje va\u017eno, dijagrami raspr\u0161enja tako\u0111er su vrlo \u010desti i koristan na\u010din pregledavanja podataka. Data scientists na\u0161iroko ih koriste kako bi vidjeli bilo kakvu postoje\u0107u korelaciju izme\u0111u skupa varijabli. Oni jednostavno ra\u0161trkaju sve to\u010dke varijable na dijagramu i ako postoji bilo kakva korelacija izme\u0111u njih, to postaje o\u010dito.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cfb2e49 elementor-widget elementor-widget-code-highlight\" data-id=\"cfb2e49\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"prismjs-default copy-to-clipboard \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-r \">\n\t\t\t\t<code readonly=\"true\" class=\"language-r\">\n\t\t\t\t\t<xmp>ggplot(data=iris, aes(x = Sepal.Length, y = Sepal.Width)) + geom_point(aes(color=Species, shape=Species)) +\r\n  xlab(\"Sepal Length\") +  ylab(\"Sepal Width\") +\r\n  ggtitle(\"Sepal Length-Width\")<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f665d29 elementor-widget elementor-widget-image\" data-id=\"f665d29\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/elementor\/thumbs\/Rplot_Scatter_Plots-qeyihkb671w47odz8wjlp5gok9gdlddqdv6ajqiz98.jpeg\" title=\"Rplot_Scatter_Plots\" alt=\"Example Scatter Plots\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-11c7237 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"11c7237\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-c72985a\" data-id=\"c72985a\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-e624fe6 elementor-widget elementor-widget-spacer\" data-id=\"e624fe6\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-274f927 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"274f927\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-66 elementor-top-column elementor-element elementor-element-626bca4\" data-id=\"626bca4\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6cfd648 elementor-widget elementor-widget-text-editor\" data-id=\"6cfd648\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h2>Regresijska analiza u R<\/h2>\r\nRegresijska analiza odnosi se na statisti\u010dku obradu gdje se identificira odnos izme\u0111u varijabli u skupu podataka. Uglavnom utvr\u0111ujemo odnos izme\u0111u nezavisnih i zavisnih varijabli, ali to ne mora uvijek biti slu\u010daj. Ovo je jo\u0161 jedna va\u017ena funkcija za naprednu analitiku s R.\r\n\r\nIdeja regresijske analize je pomo\u0107i nam da znamo kako \u0107e se druga varijabla promijeniti ako promijenimo jednu varijablu. Upravo tako se grade regresijski modeli. Postoje razli\u010dite vrste regresijskih tehnika koje mo\u017eemo koristiti na temelju oblika regresijske linije i vrsta uklju\u010denih varijabli:\r\n<ul>\r\n \t<li>Linearna regresija<\/li>\r\n \t<li>Logisti\u010dka regresija<\/li>\r\n \t<li>Multinomijalna logisti\u010dka regresija<\/li>\r\n \t<li>Redovna logisti\u010dka regresija<\/li>\r\n<\/ul>\r\nPogledajmo pobli\u017ee za \u0161to se koriste razli\u010dite vrste regresije.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-37b8c4e\" data-id=\"37b8c4e\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-0af08ca elementor-widget elementor-widget-image\" data-id=\"0af08ca\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"1024\" height=\"762\" src=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Fotolia_65676998_M-1024x762.jpg\" class=\"attachment-large size-large wp-image-33462\" alt=\"Analytics\" srcset=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Fotolia_65676998_M-1024x762.jpg 1024w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Fotolia_65676998_M-300x223.jpg 300w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Fotolia_65676998_M-768x571.jpg 768w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Fotolia_65676998_M-1536x1143.jpg 1536w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Fotolia_65676998_M.jpg 1598w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-5c55337 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"5c55337\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-7e15239\" data-id=\"7e15239\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-9ccfbf7 elementor-widget elementor-widget-text-editor\" data-id=\"9ccfbf7\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h3>1. Linearna regresija<\/h3>\r\nOvo je najosnovniji tip regresije i mo\u017ee se koristiti kada dvije varijable imaju linearni odnos. Na temelju vrijednosti dviju varijabli, ravna linija se modelira sljede\u0107om jednad\u017ebom:\r\n\r\n<em>Y = ax + b<\/em>\r\n\r\nLinearna regresija se koristi za predvi\u0111anje kontinuiranih vrijednosti gdje samo dajete vrijednost nezavisne varijable. Kao rezultat dobivate vrijednost zavisne varijable (y u ovom slu\u010daju).\r\n<h3>2. Logisti\u010dka regresija<\/h3>\r\nLogisti\u010dka regresija je sljede\u0107a tehnika regresije koja se koristi za predvi\u0111anje vrijednosti unutar odre\u0111enog raspona. Mo\u017ee se koristiti kada je ciljna varijabla kategori\u010dna, na primjer, predvi\u0111anje pobjednika ili gubitnika pomo\u0107u nekih podataka. Sljede\u0107a se jednad\u017eba koristi u logisti\u010dkoj regresiji.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-305550f elementor-widget elementor-widget-image\" data-id=\"305550f\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"155\" height=\"81\" src=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Logistic-Regression.png\" class=\"attachment-medium size-medium wp-image-33286\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ecf3000 elementor-widget elementor-widget-text-editor\" data-id=\"ecf3000\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h3>3. Multinomijalna logisti\u010dka regresija<\/h3>\r\nKao \u0161to ime sugerira, multinomijalna logisti\u010dka regresija je napredna verzija logisti\u010dke regresije. Razlika izme\u0111u ove i jednostavne logisti\u010dke regresije je u tome \u0161to mo\u017ee podr\u017eati vi\u0161e od dvije kategori\u010dke varijable. Osim toga, koristi isti mehanizam kao logisti\u010dka regresija.\r\n<h3>4. Ordinalna logisti\u010dka regresija<\/h3>\r\nOvo je tako\u0111er napredni mehanizam za jednostavnu logisti\u010dku regresiju, a koristi se za predvi\u0111anje vrijednosti koje postoje na razli\u010ditim razinama kategorija, na primjer, predvi\u0111anje rangova. Primjer primjene upotrebe ordinalne logisti\u010dke regresije bio bi ocjenjivanje va\u0161eg iskustva u restoranu.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4552d75 elementor-widget elementor-widget-spacer\" data-id=\"4552d75\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-8ebbd8a elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"8ebbd8a\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-7735a77\" data-id=\"7735a77\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4560e3c elementor-widget elementor-widget-text-editor\" data-id=\"4560e3c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h3>Kori\u0161tenje regresije u R<\/h3>\r\nSada, da vidimo kako mo\u017eemo napraviti regresijsku analizu u R. Za demonstraciju, stvorio bih logisti\u010dki regresijski model u R-u budu\u0107i da lijepo pokriva koncepte.\r\n\r\nSlu\u010daj upotrebe: Predvidjet \u0107emo uspjeh u\u010denika na ispitu koriste\u0107i njihove razine kvocijenta inteligencije.\r\n\r\nGenerirajmo neke nasumi\u010dne IQ brojeve kako bismo do\u0161li do na\u0161eg skupa podataka.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3518610 elementor-widget elementor-widget-code-highlight\" data-id=\"3518610\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"prismjs-default copy-to-clipboard \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-r \">\n\t\t\t\t<code readonly=\"true\" class=\"language-r\">\n\t\t\t\t\t<xmp># Generate random IQ values with mean = 30 and sd =2\r\nIQ <- rnorm(40, 30, 2)\r\n \r\n# Sorting IQ level in ascending order\r\nIQ <- sort(IQ)<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-10e0806 elementor-widget elementor-widget-text-editor\" data-id=\"10e0806\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\tKoriste\u0107i rnorm(), napravili smo popis od 40 IQ vrijednosti koje imaju srednju vrijednost 30 i STD 2.\r\n\r\nSada smo nasumi\u010dno kreirali vrijednosti za prolaz\/neuspjeh kao 0\/1 za 40 u\u010denika i stavili ih u dataframe. Tako\u0111er, pridru\u017eit \u0107emo svaku vrijednost koju stvorimo s IQ-om kako bi na\u0161 podatkovni okvir bio potpun.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7e0a738 elementor-widget elementor-widget-code-highlight\" data-id=\"7e0a738\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"prismjs-default copy-to-clipboard \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-r \">\n\t\t\t\t<code readonly=\"true\" class=\"language-r\">\n\t\t\t\t\t<xmp># Generate vector with pass and fail values of 40 students\r\nresult <- c(0, 0, 0, 1, 0, 0, 0, 0, 0, 1,\r\n1, 0, 0, 0, 1, 1, 0, 0, 1, 0,\r\n0, 0, 1, 0, 0, 1, 1, 0, 1, 1,\r\n1, 1, 1, 0, 1, 1, 1, 1, 0, 1)\r\n \r\n# Data Frame\r\ndf <- as.data.frame(cbind(IQ, result))\r\n \r\n# Print data frame\r\nprint(df)<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4339800 elementor-widget elementor-widget-image\" data-id=\"4339800\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"254\" src=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/blog_iq_pass_table.png\" class=\"attachment-medium_large size-medium_large wp-image-33292\" alt=\"example table\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a6a4353 elementor-widget elementor-widget-text-editor\" data-id=\"a6a4353\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\tSada napravimo regresijski model na temelju na\u0161eg skupa podataka i napravimo krivulju da vidimo kako se regresijski model pona\u0161a na njemu. Mo\u017eemo koristiti funkciju glm() za stvaranje i treniranje modela regresije i metodu curve() za crtanje krivulje na temelju predvi\u0111anja.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-774227f elementor-widget elementor-widget-code-highlight\" data-id=\"774227f\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"prismjs-default copy-to-clipboard \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-r \">\n\t\t\t\t<code readonly=\"true\" class=\"language-r\">\n\t\t\t\t\t<xmp># Plotting IQ on x-axis and result on y-axis\r\nplot(IQ, result, xlab = \"IQ Level\",\r\nylab = \"Probability of Passing\")\r\n \r\n# Create a logistic model\r\ng = glm(result~IQ, family=binomial, df)\r\n \r\n# Create a curve based on prediction using the regression model\r\ncurve(predict(g, data.frame(IQ=x), type=\"resp\"), add=TRUE)\r\n \r\n# This Draws a set of points\r\n# Based on fit to the regression model\r\npoints(IQ, fitted(g), pch=30)<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5a3aa23 elementor-widget elementor-widget-image\" data-id=\"5a3aa23\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"862\" height=\"550\" src=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_curve.jpeg\" class=\"attachment-large size-large wp-image-33299\" alt=\"regression model as graph\" srcset=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_curve.jpeg 862w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_curve-300x191.jpeg 300w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_curve-768x490.jpeg 768w\" sizes=\"(max-width: 862px) 100vw, 862px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">regression model as graph<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e02ca0c elementor-widget elementor-widget-text-editor\" data-id=\"e02ca0c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\u0160tovi\u0161e, ako \u017eelite dodatno provjeriti statistiku modela logisti\u010dke regresije, to mo\u017eete u\u010diniti pokretanjem summary() od R (summary(g)).\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f206022 elementor-widget elementor-widget-spacer\" data-id=\"f206022\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-0ed04f8 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"0ed04f8\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-1cb002e\" data-id=\"1cb002e\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-7aee867 elementor-widget elementor-widget-text-editor\" data-id=\"7aee867\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h2>Predvi\u0111anje vremenskih serija u R<\/h2>\r\nPredvi\u0111anje vremenskih serija me\u0111u najja\u010dim je odijelima R-a. Iako je Python tako\u0111er prili\u010dno poznat po analizi vremenskih serija, mnogi stru\u010dnjaci jo\u0161 uvijek tvrde da vam R pru\u017ea sveukupno bolje iskustvo. Paket prognoze je vrlo opse\u017ean, a najbolje \u0161to se mo\u017ee po\u017eeljeti za naprednu analitiku s R.\r\n\r\nU ovom \u010dlanku \u0107emo pokriti sljede\u0107e metode predvi\u0111anja vremenskih serija:\r\n<ul>\r\n \t<li>Naivne metode<\/li>\r\n \t<li>Eksponencijalno zagla\u0111ivanje<\/li>\r\n \t<li>BATS i TBATS<\/li>\r\n<\/ul>\r\nKoristit \u0107emo skup podataka Air Passengers prisutan u R-u za izradu modela na skupu za provjeru valjanosti, predvi\u0111anje trajanja skupa za provjeru valjanosti i kona\u010dno dobivanje prosje\u010dne apsolutne postotne pogre\u0161ke za zavr\u0161etak segmenta.\r\n\r\nKako bi zapo\u010deli, inicijalizirajmo podatke za treniranje i validaciju.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8f197c1 elementor-widget elementor-widget-code-highlight\" data-id=\"8f197c1\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"prismjs-default copy-to-clipboard \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-r \">\n\t\t\t\t<code readonly=\"true\" class=\"language-r\">\n\t\t\t\t\t<xmp>#  Time Series Forecast In R\r\ninstall.packages(\"forecast\")\r\ninstall.packages(\"MLmetrics\")\r\nlibrary(forecast)\r\nlibrary(MLmetrics)\r\ndata=AirPassengers\r\n#Create samples\r\ntraining=window(data, start = c(1949,1), end = c(1955,12))\r\nvalidation=window(data, start = c(1956,1))<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0dbe12a elementor-widget elementor-widget-text-editor\" data-id=\"0dbe12a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h3>1. Naivne metode<\/h3>\r\nKao \u0161to naziv govori, naivna metoda je najjednostavnija od svih metoda predvi\u0111anja. Temelji se na jednostavnom principu &#8220;ono \u0161to danas promatramo, to \u0107e biti predvi\u0111anje za sutra&#8221;. Sezonska naivna metoda je malo slo\u017eenija varijanta gdje se uzima period s kojim se radi, npr. tjedan\/mjesec\/godina.\r\n\r\nIdemo dalje sa sezonskom naivnom prognozom.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-381115d elementor-widget elementor-widget-code-highlight\" data-id=\"381115d\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"prismjs-default copy-to-clipboard \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-r \">\n\t\t\t\t<code readonly=\"true\" class=\"language-r\">\n\t\t\t\t\t<xmp>naive = snaive(training, h=length(validation))\r\nMAPE(naive$mean, validation) * 100<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-60ead3d elementor-widget elementor-widget-text-editor\" data-id=\"60ead3d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\tOvdje mo\u017eemo vidjeti MAPE rezultat od 27,05%. Idemo naprijed i zacrtajmo ovaj rezultat.\r\n\r\nMAPE rezultat = srednja apsolutna postotna pogre\u0161ka\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-439900e elementor-widget elementor-widget-code-highlight\" data-id=\"439900e\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"prismjs-default copy-to-clipboard \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-r \">\n\t\t\t\t<code readonly=\"true\" class=\"language-r\">\n\t\t\t\t\t<xmp>plot(data, col=\"blue\", xlab=\"Year\", ylab=\"Passengers\", main=\"Seasonal Naive Forecast\", type='l')\r\nlines(naive$mean, col=\"red\", lwd=2)<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0f981b9 elementor-widget elementor-widget-image\" data-id=\"0f981b9\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"490\" src=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_Seasonal_Naive_Forecast-768x490.jpeg\" class=\"attachment-medium_large size-medium_large wp-image-33314\" alt=\"plot forecast result naive forecast\" srcset=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_Seasonal_Naive_Forecast-768x490.jpeg 768w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_Seasonal_Naive_Forecast-300x191.jpeg 300w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_Seasonal_Naive_Forecast.jpeg 862w\" sizes=\"(max-width: 768px) 100vw, 768px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3c94826 elementor-widget elementor-widget-text-editor\" data-id=\"3c94826\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\tKao \u0161to mo\u017eete vidjeti, pro\u0161logodi\u0161nji skup podataka jednostavno se ponavlja za validacijski period. To je ukratko sezonska naivna prognoza za vas.\r\n<h3>2. Eksponencijalno zagla\u0111ivanje<\/h3>\r\nEksponencijalno zagla\u0111ivanje, u svojoj biti, odnosi se na smanjivanje te\u017eina opa\u017eanjima. Poput pomi\u010dnih prosjeka, najnovija opa\u017eanja dobivaju ve\u0107u te\u017einu, dok starija postupno smanjuju svoju te\u017einu, otuda i va\u017enost.\r\n\r\nDobra stvar kod paketa za predvi\u0111anje je da mo\u017eemo prona\u0107i optimalne eksponencijalne modele izravnavanja stavljanjem metoda zagla\u0111ivanja unutar strukture prostornih modela.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0171494 elementor-widget elementor-widget-code-highlight\" data-id=\"0171494\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"prismjs-default copy-to-clipboard \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-r \">\n\t\t\t\t<code readonly=\"true\" class=\"language-r\">\n\t\t\t\t\t<xmp>ets_model = ets(training, allow.multiplicative.trend = TRUE)\r\nsummary(ets_model)<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-20d48d6 elementor-widget elementor-widget-image\" data-id=\"20d48d6\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"443\" height=\"338\" src=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/summary-ets-model.png\" class=\"attachment-medium_large size-medium_large wp-image-33317\" alt=\"summary ets model\" srcset=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/summary-ets-model.png 443w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/summary-ets-model-300x229.png 300w\" sizes=\"(max-width: 443px) 100vw, 443px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">summary ets model<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-02ed5fb elementor-widget elementor-widget-text-editor\" data-id=\"02ed5fb\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\tSada \u0107emo uklju\u010diti procijenjeni model optimalnog zagla\u0111ivanje u na\u0161u ETS prognozu i vidjeti kakav \u0107e biti u\u010dinak.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f73c2d6 elementor-widget elementor-widget-code-highlight\" data-id=\"f73c2d6\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"prismjs-default copy-to-clipboard \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-r \">\n\t\t\t\t<code readonly=\"true\" class=\"language-r\">\n\t\t\t\t\t<xmp>ets_forecast = forecast(ets_model, h=length(validation))\r\nMAPE(ets_forecast$mean, validation) *100<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6a7da38 elementor-widget elementor-widget-text-editor\" data-id=\"6a7da38\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\tKao rezultat, dobivamo MAPE od 12,6%. Tako\u0111er, vidljivo je da se uzlazni trend malo ra\u010duna.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ebe5d07 elementor-widget elementor-widget-image\" data-id=\"ebe5d07\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"490\" src=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_ETS_Forecast-768x490.jpeg\" class=\"attachment-medium_large size-medium_large wp-image-33326\" alt=\"graph ETS optimized model\" srcset=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_ETS_Forecast-768x490.jpeg 768w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_ETS_Forecast-300x191.jpeg 300w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_ETS_Forecast.jpeg 862w\" sizes=\"(max-width: 768px) 100vw, 768px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-c283caf elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"c283caf\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-97d37ee\" data-id=\"97d37ee\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-798fb45 elementor-widget elementor-widget-spacer\" data-id=\"798fb45\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8db6e40 elementor-widget elementor-widget-text-editor\" data-id=\"8db6e40\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h3>3. BATS i TBATS<\/h3>\r\nZa procese koji imaju vrlo slo\u017eene trendove, ETS \u010desto nije dovoljno dobar. Ponekad mo\u017eete imati i tjednu i godi\u0161nju sezonalnost, a tu se isti\u010du BATS i TBATS jer se mogu nositi s vi\u0161e sezonalnosti odjednom.\r\n\r\nIzgradimo TBATS model i napravimo predvi\u0111anje.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6ce40b1 elementor-widget elementor-widget-code-highlight\" data-id=\"6ce40b1\" data-element_type=\"widget\" data-widget_type=\"code-highlight.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"prismjs-default copy-to-clipboard \">\n\t\t\t<pre data-line=\"\" class=\"highlight-height language-r \">\n\t\t\t\t<code readonly=\"true\" class=\"language-r\">\n\t\t\t\t\t<xmp>tbats_model = tbats(training)\r\ntbats_forecast = forecast(tbats_model, h=length(validation))\r\nMAPE(tbats_forecast$mean, validation) * 100\r\n\r\nplot(data, col=\"blue\", xlab=\"Year\", ylab=\"Passengers\", main=\"ETS Forecast\", type='l')\r\nlines(tbats_forecast$mean, col=\"red\", lwd=2)<\/xmp>\n\t\t\t\t<\/code>\n\t\t\t<\/pre>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-543e787 elementor-widget elementor-widget-image\" data-id=\"543e787\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"490\" src=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_tbats_forecast-768x490.jpeg\" class=\"attachment-medium_large size-medium_large wp-image-33335\" alt=\"graph TBATS Forecast\" srcset=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_tbats_forecast-768x490.jpeg 768w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_tbats_forecast-300x191.jpeg 300w, https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_tbats_forecast.jpeg 862w\" sizes=\"(max-width: 768px) 100vw, 768px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0269892 elementor-widget elementor-widget-text-editor\" data-id=\"0269892\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\tKao \u0161to mo\u017eete vidjeti, MAPE od 12,9% posti\u017ee se ovom metodom.\r\n\r\nZaklju\u010dak\r\nTo je sve za danas! Nau\u010dili smo o naprednoj analitici u R-u koja se usredoto\u010duje na crtanje i razli\u010dite vrste regresijske analitike te smo dalje obra\u0111ivali prognozu vremenskih serija u R. Me\u0111utim, vremenske serije su prili\u010dno opse\u017ena tema sama po sebi i jo\u0161 smo samo zagrebali povr\u0161inu. Stoga ostanite s nama jer \u0107emo Time Series detaljno obra\u0111ivati u nadolaze\u0107im blogovima.\r\n\r\nDo tada, sretan R-ing de\u010dki!\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>U ovom blogu pokazujemo koliko je jednostavno koristiti funkcije napredne analitike u R. Fokusiramo se na razli\u010dite vrste dijagrama, regresijsku analizu s R i prognozu vremenske serije s R.<\/p>\n","protected":false},"author":13,"featured_media":33336,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[508,544],"tags":[45,555],"class_list":["post-34071","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-business-analytics","category-business-analytics-plattform","tag-business-analytics-platform","tag-r"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v24.6) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Napredna analiza s R: Pregled - CubeServ<\/title>\n<meta name=\"description\" content=\"U ovom blogu pokazujemo koliko je jednostavno koristiti funkcije napredne analitike u R-u kao \u0161to je regresijska analiza s R-om i predvi\u0111anje vremenskog niza s R-om.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.cubeserv.com\/hr\/napredna-analitika-s-r-pregled\/\" \/>\n<meta property=\"og:locale\" content=\"hr_HR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Napredna analiza s R: Pregled\" \/>\n<meta property=\"og:description\" content=\"U ovom blogu pokazujemo koliko je jednostavno koristiti funkcije napredne analitike u R-u kao \u0161to je regresijska analiza s R-om i predvi\u0111anje vremenskog niza s R-om.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.cubeserv.com\/hr\/napredna-analitika-s-r-pregled\/\" \/>\n<meta property=\"og:site_name\" content=\"CubeServ\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/CubeServ\" \/>\n<meta property=\"article:published_time\" content=\"2022-02-25T09:06:00+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2022-06-06T21:07:11+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_tbats_forecast.jpeg\" \/>\n\t<meta property=\"og:image:width\" content=\"862\" \/>\n\t<meta property=\"og:image:height\" content=\"550\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Adrian Bourcevet\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@CubeServ\" \/>\n<meta name=\"twitter:site\" content=\"@CubeServ\" \/>\n<meta name=\"twitter:label1\" content=\"Napisao\/la\" \/>\n\t<meta name=\"twitter:data1\" content=\"Adrian Bourcevet\" \/>\n\t<meta name=\"twitter:label2\" content=\"Procijenjeno vrijeme \u010ditanja\" \/>\n\t<meta name=\"twitter:data2\" content=\"9 minuta\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.cubeserv.com\/hr\/napredna-analitika-s-r-pregled\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.cubeserv.com\/hr\/napredna-analitika-s-r-pregled\/\"},\"author\":{\"name\":\"Adrian Bourcevet\",\"@id\":\"https:\/\/www.cubeserv.com\/hr\/#\/schema\/person\/574e60369373adc3dfa856f4ba151e3d\"},\"headline\":\"Napredna analiza s R: Pregled\",\"datePublished\":\"2022-02-25T09:06:00+00:00\",\"dateModified\":\"2022-06-06T21:07:11+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.cubeserv.com\/hr\/napredna-analitika-s-r-pregled\/\"},\"wordCount\":1455,\"publisher\":{\"@id\":\"https:\/\/www.cubeserv.com\/hr\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.cubeserv.com\/hr\/napredna-analitika-s-r-pregled\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.cubeserv.com\/wp-content\/uploads\/2022\/02\/Rplot_tbats_forecast.jpeg\",\"keywords\":[\"Business Analytics Platform\",\"R\"],\"articleSection\":[\"Business Analytics\",\"Business Analytics Plattform\"],\"inLanguage\":\"hr\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.cubeserv.com\/hr\/napredna-analitika-s-r-pregled\/\",\"url\":\"https:\/\/www.cubeserv.com\/hr\/napredna-analitika-s-r-pregled\/\",\"name\":\"Napredna analiza s R: Pregled - 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