{"id":8410,"date":"2020-03-27T17:24:33","date_gmt":"2020-03-27T16:24:33","guid":{"rendered":"https:\/\/complex-systems-ai.com\/?page_id=8410"},"modified":"2024-02-25T18:31:59","modified_gmt":"2024-02-25T17:31:59","slug":"criteres-de-qualite-externes","status":"publish","type":"page","link":"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/","title":{"rendered":"Criterios de calidad externos"},"content":{"rendered":"<div data-elementor-type=\"wp-page\" data-elementor-id=\"8410\" class=\"elementor elementor-8410\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-1a27ac6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1a27ac6\" data-element_type=\"section\" data-e-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-33 elementor-top-column elementor-element elementor-element-6d0e1cd\" data-id=\"6d0e1cd\" data-element_type=\"column\" data-e-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-da704fb elementor-align-justify elementor-widget elementor-widget-button\" data-id=\"da704fb\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Partici\u00f3n de datos<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\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-617ece0\" data-id=\"617ece0\" data-element_type=\"column\" data-e-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-ab74984 elementor-align-justify elementor-widget elementor-widget-button\" data-id=\"ab74984\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/complex-systems-ai.com\/es\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Pagina de inicio<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\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-41c3717\" data-id=\"41c3717\" data-element_type=\"column\" data-e-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-37b4c99 elementor-align-justify elementor-widget elementor-widget-button\" data-id=\"37b4c99\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/en.wikipedia.org\/wiki\/Cluster_analysis\" target=\"_blank\" rel=\"noopener\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Wiki<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\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-783e2e4 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"783e2e4\" data-element_type=\"section\" data-e-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-0bc361c\" data-id=\"0bc361c\" data-element_type=\"column\" data-e-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-636ba42 elementor-widget elementor-widget-heading\" data-id=\"636ba42\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Contenido<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Tabla de contenido alternativo\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Palanca<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Criteres-de-qualite-externes\" >Criterios de calidad externos<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Liste\" >Lista<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Notation\" >Clasificaci\u00f3n<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Mesure-de-rappel-de-precision-et-F-mesure\" >Medici\u00f3n de recuperaci\u00f3n de precisi\u00f3n y medida F<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Variables-indicatrices\" >Variables indicadoras<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Mesure-fondee-sur-linformation-mutuelle\" >Medida basada en informaci\u00f3n mutua<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Entropie-purete-et-V-mesure\" >Entrop\u00eda, pureza y medida V<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Czekanowski-Dice\" >Dados Czekanowski<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Folkes-Mallows\" >Folkes-Mallows<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Hubert-%CE%93\" >Hubert \u0393<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Jaccard\" >jaccard<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Kulczynski\" >kulczynski<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#McNemar\" >Mc Nemar<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Phi\" >Fi<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Rand\" >rand<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Rogers-Tanimoto\" >Rogers-Tanimoto<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Russel-Rao\" >Russell Rao<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/criterios-de-calidad-externos\/#Sokal-Sneath\" >Sokal-Sneath<\/a><\/li><\/ul><\/nav><\/div>\n<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Criteres-de-qualite-externes\"><\/span>Criterios de calidad externos<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-c0ca37d elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"c0ca37d\" data-element_type=\"section\" data-e-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-30e8c37\" data-id=\"30e8c37\" data-element_type=\"column\" data-e-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-2720cf2 elementor-widget elementor-widget-text-editor\" data-id=\"2720cf2\" data-element_type=\"widget\" data-e-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<p>Los \u00edndices de calidad externa son \u00edndices destinados a medir la similitud entre dos particiones. S\u00f3lo tienen en cuenta la distribuci\u00f3n de puntos en los diferentes clusters y no permiten medir la calidad de esta distribuci\u00f3n.<\/p>\n<p><img decoding=\"async\" class=\"aligncenter wp-image-11096 size-full\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2020\/09\/cropped-Capture.png\" alt=\"criterios de calidad externos\" width=\"97\" height=\"97\" title=\"\"><\/p>\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-1d82c86 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1d82c86\" data-element_type=\"section\" data-e-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-013fc7f\" data-id=\"013fc7f\" data-element_type=\"column\" data-e-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-236e726 elementor-widget elementor-widget-heading\" data-id=\"236e726\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Liste\"><\/span>Lista<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-c8d47da elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"c8d47da\" data-element_type=\"section\" data-e-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-b75e1e8\" data-id=\"b75e1e8\" data-element_type=\"column\" data-e-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-6c8adb7 elementor-widget elementor-widget-text-editor\" data-id=\"6c8adb7\" data-element_type=\"widget\" data-e-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<ul>\n<li>Medici\u00f3n de recuperaci\u00f3n de precisi\u00f3n<\/li>\n<li>Variables indicadoras<\/li>\n<li>Medida basada en informaci\u00f3n mutua<\/li>\n<li>Entrop\u00eda, pureza y medida V<\/li>\n<li>Dados Czekanowski<\/li>\n<li>Folkes-Mallows<\/li>\n<li>Hubert \u0393<\/li>\n<li><a href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/funcion-de-similitud\/\">jaccard<\/a><\/li>\n<li>kulczynski<\/li>\n<li>Mc Nemar<\/li>\n<li>Fi<\/li>\n<li>rand<\/li>\n<li>Rogers-Tanimoto<\/li>\n<li>Russell Rao<\/li>\n<li>Sokal-Sneath<\/li>\n<\/ul>\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-0806166 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"0806166\" data-element_type=\"section\" data-e-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-f3d6ea9\" data-id=\"f3d6ea9\" data-element_type=\"column\" data-e-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-714ed91 elementor-widget elementor-widget-heading\" data-id=\"714ed91\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Notation\"><\/span>Clasificaci\u00f3n<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-798ca46 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"798ca46\" data-element_type=\"section\" data-e-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-2d7ebed\" data-id=\"2d7ebed\" data-element_type=\"column\" data-e-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-9406cbf elementor-widget elementor-widget-text-editor\" data-id=\"9406cbf\" data-element_type=\"widget\" data-e-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<p>Todos los \u00edndices propuestos se basan en una matriz de confusi\u00f3n que representa el c\u00f3mputo de pares de puntos en funci\u00f3n de si se consideran pertenecientes o no al mismo cluster seg\u00fan la partici\u00f3n P1 o la partici\u00f3n P2. Por tanto, existen cuatro posibilidades:<\/p>\n<p>\u2022 los dos puntos pertenecen al mismo grupo, seg\u00fan P1 y P2<\/p>\n<p>\u2022 los dos puntos pertenecen al mismo grupo seg\u00fan P1 pero no seg\u00fan P2<\/p>\n<p>\u2022 los dos puntos pertenecen al mismo grupo seg\u00fan P2 pero no seg\u00fan P1<\/p>\n<p>\u2022 los dos puntos no pertenecen al mismo grupo, seg\u00fan P1 y P2.<\/p>\n<p>Anotemos yy, yn, ny, nn (y significa s\u00ed y n significa no) el n\u00famero de puntos que pertenecen respectivamente a estas cuatro categor\u00edas. Siendo NT el n\u00famero total de pares de puntos, tenemos:<\/p>\n<p><img decoding=\"async\" class=\"alignnone size-full wp-image-21118\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Qualite_externe1.png\" alt=\"calidad externa\" width=\"272\" height=\"44\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Qualite_externe1.png 272w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Qualite_externe1-18x3.png 18w\" sizes=\"(max-width: 272px) 100vw, 272px\" \/><\/p>\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-0e5dc61 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"0e5dc61\" data-element_type=\"section\" data-e-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-fa5a643\" data-id=\"fa5a643\" data-element_type=\"column\" data-e-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-afd84a3 elementor-widget elementor-widget-heading\" data-id=\"afd84a3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Mesure-de-rappel-de-precision-et-F-mesure\"><\/span>Medici\u00f3n de recuperaci\u00f3n de precisi\u00f3n y medida F<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-2507304 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"2507304\" data-element_type=\"section\" data-e-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-0a81bad\" data-id=\"0a81bad\" data-element_type=\"column\" data-e-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-32cf5be elementor-widget elementor-widget-text-editor\" data-id=\"32cf5be\" data-element_type=\"widget\" data-e-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<p>Si se utiliza la partici\u00f3n P1 como referencia, definimos el coeficiente de precisi\u00f3n como la proporci\u00f3n de puntos precisamente agrupados en P2, es decir que tambi\u00e9n est\u00e1n agrupados seg\u00fan la partici\u00f3n de referencia P1. Entre los puntos yy + ny agrupados seg\u00fan P2, yy est\u00e1n correctamente agrupados. Entonces tenemos :<\/p>\n<p><img decoding=\"async\" class=\"alignnone size-full wp-image-21119\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/precision_recall1.png\" alt=\"recuperaci\u00f3n de precisi\u00f3n\" width=\"97\" height=\"42\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/precision_recall1.png 97w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/precision_recall1-18x8.png 18w\" sizes=\"(max-width: 97px) 100vw, 97px\" \/><\/p>\n<p>Asimismo, definimos el coeficiente de recuperaci\u00f3n como la proporci\u00f3n de puntos agrupados en P1 que tambi\u00e9n lo est\u00e1n en la partici\u00f3n P2. Se trata de la proporci\u00f3n de puntos que se supone que est\u00e1n agrupados seg\u00fan la partici\u00f3n de referencia P1 y que en realidad est\u00e1n identificados como tales por la partici\u00f3n P2. Entre los puntos yy+yn agrupados en P1, yy tambi\u00e9n est\u00e1n agrupados en P2. Entonces tenemos :<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21120\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/precision_recall2.png\" alt=\"recuperaci\u00f3n de precisi\u00f3n\" width=\"110\" height=\"44\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/precision_recall2.png 110w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/precision_recall2-18x7.png 18w\" sizes=\"(max-width: 110px) 100vw, 110px\" \/><\/p>\n<p>En t\u00e9rminos de probabilidades condicionales, podemos escribir<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21121\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/precision_recall3.png\" alt=\"recuperaci\u00f3n de precisi\u00f3n\" width=\"283\" height=\"38\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/precision_recall3.png 283w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/precision_recall3-18x2.png 18w\" sizes=\"(max-width: 283px) 100vw, 283px\" \/><\/p>\n<p>donde los eventos gp1 y gp2 significan que dos puntos se agrupan en P1 y P2 respectivamente.<\/p>\n<p>La medida F es el promedio arm\u00f3nico de los coeficientes de precisi\u00f3n y recuperaci\u00f3n:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-21122\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/F-mesure1-300x66.png\" alt=\"Medida F\" width=\"300\" height=\"66\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/F-mesure1-300x66.png 300w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/F-mesure1-18x4.png 18w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/F-mesure1.png 307w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>Tambi\u00e9n existe una versi\u00f3n ponderada de esta medida, llamada medida F\u03b1, definida de la siguiente manera:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21123\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/F-mesure2.png\" alt=\"Medida F\" width=\"225\" height=\"51\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/F-mesure2.png 225w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/F-mesure2-18x4.png 18w\" sizes=\"(max-width: 225px) 100vw, 225px\" \/><\/p>\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-bbb39b3 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"bbb39b3\" data-element_type=\"section\" data-e-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-eff761b\" data-id=\"eff761b\" data-element_type=\"column\" data-e-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-7b17aee elementor-widget elementor-widget-heading\" data-id=\"7b17aee\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Variables-indicatrices\"><\/span>Variables indicadoras<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-6c2e23a elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6c2e23a\" data-element_type=\"section\" data-e-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-4070894\" data-id=\"4070894\" data-element_type=\"column\" data-e-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-8853e15 elementor-widget elementor-widget-text-editor\" data-id=\"8853e15\" data-element_type=\"widget\" data-e-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<p>Asociemos a cada partici\u00f3n Pa (a = 1, 2) la variable aleatoria binaria Xa definida sobre el conjunto de \u00edndices i y j tal que i &lt; j de la siguiente manera: su valor es 1 si los puntos Mi y Mj est\u00e1n clasificados en la mismo cl\u00faster solo en la partici\u00f3n Pa y 0 en caso contrario. La variable Xa funciona como variable indicadora.<\/p>\n<p>Existen NT pares de puntos y s\u00f3lo nos interesan los \u00edndices i y j tales que i &lt; j. Considere la media y la desviaci\u00f3n est\u00e1ndar de Xa:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21128\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Qualite_externe2.png\" alt=\"Calidad externa\" width=\"251\" height=\"98\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Qualite_externe2.png 251w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Qualite_externe2-18x7.png 18w\" sizes=\"(max-width: 251px) 100vw, 251px\" \/><\/p>\n<p>Las siguientes f\u00f3rmulas relacionan estas variables aleatorias con las variables de conteo coincidentes y discordantes:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21129\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Qualite_externe3.png\" alt=\"Calidad externa\" width=\"240\" height=\"136\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Qualite_externe3.png 240w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Qualite_externe3-18x10.png 18w\" sizes=\"(max-width: 240px) 100vw, 240px\" \/><\/p>\n<p>De aqu\u00ed obtenemos:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-21130 size-full\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Qualite_externe4.png\" alt=\"Calidad externa\" width=\"400\" height=\"82\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Qualite_externe4.png 400w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Qualite_externe4-300x62.png 300w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Qualite_externe4-18x4.png 18w\" sizes=\"(max-width: 400px) 100vw, 400px\" \/><\/p>\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-ff81926 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"ff81926\" data-element_type=\"section\" data-e-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-7d83f46\" data-id=\"7d83f46\" data-element_type=\"column\" data-e-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-b3c4490 elementor-widget elementor-widget-heading\" data-id=\"b3c4490\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Mesure-fondee-sur-linformation-mutuelle\"><\/span>Medida basada en informaci\u00f3n mutua<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-43c26d7 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"43c26d7\" data-element_type=\"section\" data-e-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-ca01066\" data-id=\"ca01066\" data-element_type=\"column\" data-e-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-d855bc2 elementor-widget elementor-widget-text-editor\" data-id=\"d855bc2\" data-element_type=\"widget\" data-e-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<p>El criterio de informaci\u00f3n mutua se puede utilizar como una medida externa para la agrupaci\u00f3n. La medida para m instancias agrupadas usando C = {C_1,. . . , C_g} y se refiere al atributo objetivo y cuyo dominio es dom (y) = {c_1,. . . , c_k} se define de la siguiente manera:<\/p>\n<p><!-- \/wp:paragraph --><!-- wp:image {\"sizeSlug\":\"large\"} --><\/p>\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone\" src=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2020\/03\/eval16.png\" alt=\"Criterios de calidad externos (medici\u00f3n basada en informaci\u00f3n mutua, medici\u00f3n de recuperaci\u00f3n de precisi\u00f3n, \u00edndice RAND)\" width=\"325\" height=\"68\" title=\"\"><\/figure>\n<p><!-- \/wp:image --><!-- wp:paragraph --><\/p>\n<p>donde m_l, h indica el n\u00famero de instancias que est\u00e1n en el cl\u00faster C_l y tambi\u00e9n en la clase c_h. m., h indica el n\u00famero total de instancias en la clase c_h. Asimismo, m_l,. indica el n\u00famero de instancias del cl\u00faster C_l.<\/p>\n<p><!-- \/wp:paragraph --><!-- wp:paragraph --><\/p>\n<p>MI se combina con entrop\u00eda en el NMI:<\/p>\n<p><!-- \/wp:paragraph --><!-- wp:image {\"sizeSlug\":\"large\"} --><\/p>\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone\" src=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2020\/03\/eval33.png\" alt=\"Criterios de calidad externos (medici\u00f3n basada en informaci\u00f3n mutua, medici\u00f3n de recuperaci\u00f3n de precisi\u00f3n, \u00edndice RAND)\" width=\"292\" height=\"69\" title=\"\"><\/figure>\n<p><!-- \/wp:image --><!-- wp:paragraph --><\/p>\n<p>MI se combina con entrop\u00eda en AMI:<\/p>\n<p><!-- \/wp:paragraph --><!-- wp:image {\"sizeSlug\":\"large\"} --><\/p>\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone\" src=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2020\/03\/eval32.png\" alt=\"Criterios de calidad externos (medici\u00f3n basada en informaci\u00f3n mutua, medici\u00f3n de recuperaci\u00f3n de precisi\u00f3n, \u00edndice RAND)\" width=\"441\" height=\"68\" title=\"\"><\/figure>\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-a093d54 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"a093d54\" data-element_type=\"section\" data-e-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-643b842\" data-id=\"643b842\" data-element_type=\"column\" data-e-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-6184715 elementor-widget elementor-widget-heading\" data-id=\"6184715\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Entropie-purete-et-V-mesure\"><\/span>Entrop\u00eda, pureza y medida V<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-b816b87 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"b816b87\" data-element_type=\"section\" data-e-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-f47693b\" data-id=\"f47693b\" data-element_type=\"column\" data-e-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-0e131ae elementor-widget elementor-widget-text-editor\" data-id=\"0e131ae\" data-element_type=\"widget\" data-e-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<p>Dado que el cl\u00faster completo (todos los objetos de una misma clase se asignan a un solo cl\u00faster) y el cl\u00faster homog\u00e9neo (cada cl\u00faster contiene solo objetos de la misma clase) rara vez se logran, nuestro objetivo es lograr un equilibrio satisfactorio entre estos dos enfoques. Por lo tanto, generalmente aplicamos cinco criterios de agrupaci\u00f3n bien conocidos para evaluar el rendimiento de la partici\u00f3n, que son la pureza, la entrop\u00eda H, la m\u00e9trica V, el \u00edndice RAND y la m\u00e9trica F. Esta p\u00e1gina expone los tres primeros. Los dem\u00e1s est\u00e1n expuestos en otra p\u00e1gina.<\/p>\n<p>La medida de entrop\u00eda se usa para mostrar c\u00f3mo se dividen los grupos de oraciones dentro de cada grupo, y se conoce como el promedio de los valores ponderados en cada grupo de entrop\u00eda sobre todos los grupos C = {c_1, \u2026, c_n}:<\/p>\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone\" title=\"Entrop\u00eda, pureza y entrop\u00eda de medida V\" src=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2020\/03\/eval28-1.png\" alt=\"Pureza de entrop\u00eda y medida V\" width=\"452\" height=\"90\" \/><\/figure>\n<p>La pureza de un grupo es la fracci\u00f3n del tama\u00f1o del grupo representado por la clase m\u00e1s grande de oraciones asignadas a este grupo, a saber:<\/p>\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone\" title=\"Entrop\u00eda, pureza y entrop\u00eda de medida V\" src=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2020\/03\/eval29.png\" alt=\"Pureza de entrop\u00eda y medida V\" width=\"210\" height=\"65\" \/><\/figure>\n<p>La pureza general es la suma ponderada de las purezas de los grupos individuales dada por:<\/p>\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone\" title=\"Entrop\u00eda, pureza y entrop\u00eda de medida V\" src=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2020\/03\/eval30.png\" alt=\"Pureza de entrop\u00eda y medida V\" width=\"218\" height=\"72\" \/><\/figure>\n<p>Aunque la pureza y la entrop\u00eda son \u00fatiles para comparar\u00a0<a href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/\">fraccionamiento<\/a>\u00a0con el mismo\u00a0<a href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/calidad-sobre-numero-de-clusteres\/\">n\u00famero de grupos<\/a>, no son confiables al comparar <a href=\"https:\/\/complex-systems-ai.com\/es\/particionamiento-de-datos\/\">fraccionamiento<\/a> con diferente n\u00famero de conglomerados. Esto se debe a que la entrop\u00eda y la pureza influyen en c\u00f3mo se dividen los conjuntos de oraciones dentro de cada grupo, y esto conducir\u00e1 a un caso de homogeneidad. Los puntajes de pureza m\u00e1s altos y los puntajes de entrop\u00eda m\u00e1s bajos generalmente se obtienen cuando el n\u00famero total de grupos es demasiado grande, donde este paso conducir\u00e1 a ser el m\u00e1s bajo en integridad. La siguiente medida considera tanto el enfoque de integridad como el de homogeneidad.<\/p>\n<p>La medida V se conoce como la media arm\u00f3nica de homogeneidad y completitud; es decir, V = homogeneidad * completitud \/ (homogeneidad + completitud), donde homogeneidad y completitud se definen como homogeneidad = 1-H (C | L) \/ H (C) y completitud = 1-H (L | C) \/ H (B) donde:<\/p>\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone\" title=\"Entrop\u00eda, pureza y entrop\u00eda de medida V\" src=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2020\/03\/eval31.png\" alt=\"Pureza de entrop\u00eda y medida V\" width=\"690\" height=\"152\" \/><\/figure>\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-9dd4f5e elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"9dd4f5e\" data-element_type=\"section\" data-e-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-bd8bb45\" data-id=\"bd8bb45\" data-element_type=\"column\" data-e-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-f32762d elementor-widget elementor-widget-heading\" data-id=\"f32762d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Czekanowski-Dice\"><\/span>Dados Czekanowski<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-3efeb3b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3efeb3b\" data-element_type=\"section\" data-e-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-9537368\" data-id=\"9537368\" data-element_type=\"column\" data-e-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-4f52771 elementor-widget elementor-widget-text-editor\" data-id=\"4f52771\" data-element_type=\"widget\" data-e-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<p>El \u00edndice de Czekanowski-Dice (tambi\u00e9n conocido como \u00edndice de Ochiai) se define as\u00ed:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21131\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Czekanowski-Dice1.png\" alt=\"Dados Czekanowski\" width=\"132\" height=\"39\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Czekanowski-Dice1.png 132w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Czekanowski-Dice1-18x5.png 18w\" sizes=\"(max-width: 132px) 100vw, 132px\" \/><\/p>\n<p>Este \u00edndice es el promedio arm\u00f3nico de los coeficientes de precisi\u00f3n y recuperaci\u00f3n, es decir, es id\u00e9ntico a la medida F:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21132\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Czekanowski-Dice2.png\" alt=\"Dados Czekanowski\" width=\"105\" height=\"41\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Czekanowski-Dice2.png 105w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Czekanowski-Dice2-18x7.png 18w\" sizes=\"(max-width: 105px) 100vw, 105px\" \/><\/p>\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-cf60f1a elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"cf60f1a\" data-element_type=\"section\" data-e-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-4fbee6d\" data-id=\"4fbee6d\" data-element_type=\"column\" data-e-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-1e424b2 elementor-widget elementor-widget-heading\" data-id=\"1e424b2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Folkes-Mallows\"><\/span>Folkes-Mallows<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-e190e05 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"e190e05\" data-element_type=\"section\" data-e-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-87d8efc\" data-id=\"87d8efc\" data-element_type=\"column\" data-e-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-57dbe89 elementor-widget elementor-widget-text-editor\" data-id=\"57dbe89\" data-element_type=\"widget\" data-e-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<p>El \u00edndice de Folkes-Mallows se define de la siguiente manera:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21133\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Folkes-Mallows.png\" alt=\"Folkes-Mallows\" width=\"196\" height=\"38\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Folkes-Mallows.png 196w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Folkes-Mallows-18x3.png 18w\" sizes=\"(max-width: 196px) 100vw, 196px\" \/><\/p>\n<p>Este \u00edndice es la media geom\u00e9trica (ra\u00edz cuadrada de la multiplicaci\u00f3n) de los coeficientes de precisi\u00f3n y recuperaci\u00f3n.<\/p>\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-94da3b6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"94da3b6\" data-element_type=\"section\" data-e-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-df91ace\" data-id=\"df91ace\" data-element_type=\"column\" data-e-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-01835a6 elementor-widget elementor-widget-heading\" data-id=\"01835a6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Hubert-%CE%93\"><\/span>Hubert \u0393<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-2c575e6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"2c575e6\" data-element_type=\"section\" data-e-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-0529dec\" data-id=\"0529dec\" data-element_type=\"column\" data-e-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-34bd208 elementor-widget elementor-widget-text-editor\" data-id=\"34bd208\" data-element_type=\"widget\" data-e-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<p>El \u00edndice de Hubert \u02c6\u0393 es el coeficiente de <a href=\"https:\/\/complex-systems-ai.com\/es\/correlacion-y-regresiones\/\">correlaci\u00f3n<\/a> variables indicadoras. Se define de la siguiente manera:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-21134 size-full\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Hubert1.png\" alt=\"Hubert Gamma\" width=\"386\" height=\"60\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Hubert1.png 386w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Hubert1-300x47.png 300w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Hubert1-18x3.png 18w\" sizes=\"(max-width: 386px) 100vw, 386px\" \/><\/p>\n<p>El \u00edndice de Hubert \u02c6\u0393 aparece como una variante estandarizada (centrada y reducida) del \u00edndice de Russell-Rao. Su valor est\u00e1 entre -1 y 1. Podemos escribir el \u00edndice \u02c6\u0393 de la siguiente manera:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-21135\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Hubert2-300x55.png\" alt=\"Hubert Gamma\" width=\"300\" height=\"55\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Hubert2-300x55.png 300w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Hubert2-18x3.png 18w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Hubert2.png 328w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/p>\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-fb9d6c9 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"fb9d6c9\" data-element_type=\"section\" data-e-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-7a936e6\" data-id=\"7a936e6\" data-element_type=\"column\" data-e-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-9587eb8 elementor-widget elementor-widget-heading\" data-id=\"9587eb8\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Jaccard\"><\/span>jaccard<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-3437e5a elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3437e5a\" data-element_type=\"section\" data-e-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-d5fc1e6\" data-id=\"d5fc1e6\" data-element_type=\"column\" data-e-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-55a0800 elementor-widget elementor-widget-text-editor\" data-id=\"55a0800\" data-element_type=\"widget\" data-e-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<p>El \u00edndice Jaccard se define de la siguiente manera:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21136\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Jaccard.png\" alt=\"jaccard\" width=\"139\" height=\"35\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Jaccard.png 139w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Jaccard-18x5.png 18w\" sizes=\"(max-width: 139px) 100vw, 139px\" \/><\/p>\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-3934b78 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3934b78\" data-element_type=\"section\" data-e-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-c534c01\" data-id=\"c534c01\" data-element_type=\"column\" data-e-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-e279b70 elementor-widget elementor-widget-heading\" data-id=\"e279b70\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Kulczynski\"><\/span>kulczynski<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-32354b9 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"32354b9\" data-element_type=\"section\" data-e-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-9340501\" data-id=\"9340501\" data-element_type=\"column\" data-e-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-ab9b493 elementor-widget elementor-widget-text-editor\" data-id=\"ab9b493\" data-element_type=\"widget\" data-e-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<p>El \u00edndice de Kulczynski se define de la siguiente manera:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21137\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Kulczynski.png\" alt=\"kulczynski\" width=\"192\" height=\"41\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Kulczynski.png 192w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Kulczynski-18x4.png 18w\" sizes=\"(max-width: 192px) 100vw, 192px\" \/><\/p>\n<p>Este \u00edndice es el promedio aritm\u00e9tico de los coeficientes de precisi\u00f3n y recuperaci\u00f3n.<\/p>\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-c8121ba elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"c8121ba\" data-element_type=\"section\" data-e-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-8cc549e\" data-id=\"8cc549e\" data-element_type=\"column\" data-e-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-90ceaa7 elementor-widget elementor-widget-heading\" data-id=\"90ceaa7\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"McNemar\"><\/span>Mc Nemar<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-f088d4a elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f088d4a\" data-element_type=\"section\" data-e-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-f8cbc20\" data-id=\"f8cbc20\" data-element_type=\"column\" data-e-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-f91fe22 elementor-widget elementor-widget-text-editor\" data-id=\"f91fe22\" data-element_type=\"widget\" data-e-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<p>El \u00edndice de McNemar se define de la siguiente manera:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21138\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/McNemar1.png\" alt=\"Mc Nemar\" width=\"100\" height=\"39\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/McNemar1.png 100w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/McNemar1-18x7.png 18w\" sizes=\"(max-width: 100px) 100vw, 100px\" \/><\/p>\n<p>Bajo la hip\u00f3tesis nula H0 de que los desajustes entre las particiones P1 y P2 son aleatorios, el \u00edndice C sigue aproximadamente una distribuci\u00f3n normal. Esta es una adaptaci\u00f3n de la prueba no param\u00e9trica de McNemar para comparar frecuencias entre dos muestras pareadas: el estad\u00edstico de la prueba de McNemar (llamado distancia \u03c72) es el cuadrado del \u00edndice:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21139\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/McNemar2.png\" alt=\"Mc Nemar\" width=\"128\" height=\"46\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/McNemar2.png 128w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/McNemar2-18x6.png 18w\" sizes=\"(max-width: 128px) 100vw, 128px\" \/><\/p>\n<p>y sigue, bajo la hip\u00f3tesis nula de homogeneidad marginal de la tabla de contingencia, una distribuci\u00f3n Chi-cuadrado con 1 grado de libertad.<\/p>\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-bf4ac82 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"bf4ac82\" data-element_type=\"section\" data-e-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-a121d9d\" data-id=\"a121d9d\" data-element_type=\"column\" data-e-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-ab5a9c4 elementor-widget elementor-widget-heading\" data-id=\"ab5a9c4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Phi\"><\/span>Fi<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-bba9fdd elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"bba9fdd\" data-element_type=\"section\" data-e-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-fe849fd\" data-id=\"fe849fd\" data-element_type=\"column\" data-e-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-686b4fd elementor-widget elementor-widget-text-editor\" data-id=\"686b4fd\" data-element_type=\"widget\" data-e-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<p>El \u00edndice Phi es una medida cl\u00e1sica de la correlaci\u00f3n entre dos variables dicot\u00f3micas. Se define de la siguiente manera:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21140\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Phi.png\" alt=\"Fi\" width=\"293\" height=\"36\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Phi.png 293w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Phi-18x2.png 18w\" sizes=\"(max-width: 293px) 100vw, 293px\" \/><\/p>\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-2f809ec elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"2f809ec\" data-element_type=\"section\" data-e-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-26e71d7\" data-id=\"26e71d7\" data-element_type=\"column\" data-e-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-1519600 elementor-widget elementor-widget-heading\" data-id=\"1519600\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Rand\"><\/span>rand<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-67d92a4a elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"67d92a4a\" data-element_type=\"section\" data-e-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-6519ef83\" data-id=\"6519ef83\" data-element_type=\"column\" data-e-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-1f15dfbf elementor-widget elementor-widget-text-editor\" data-id=\"1f15dfbf\" data-element_type=\"widget\" data-e-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<!-- wp:paragraph --><!-- \/wp:heading --><!-- wp:paragraph -->\n<figure class=\"wp-block-image size-large\"><\/figure>\n<!-- \/wp:image --><!-- wp:heading --><!-- \/wp:heading --><!-- wp:paragraph --><!-- \/wp:heading --><!-- wp:paragraph -->\n<p>El \u00edndice Rand es un criterio simple que se utiliza para comparar una estructura de agregaci\u00f3n inducida (C1) con una estructura de agregaci\u00f3n dada (C2). Sea a el n\u00famero de pares de instancias asignados al mismo grupo en C1 y en el mismo grupo en C2; sea b el n\u00famero de pares de instancias que est\u00e1n en el mismo grupo C1, pero no en el mismo grupo C2; sea c el n\u00famero de pares de instancias que est\u00e1n en el mismo grupo C2, pero no en el mismo grupo C1; yd el n\u00famero de pares de instancias asignados a diferentes cl\u00fasteres que C1 y C2.<\/p>\n<p>Las cantidades ayd se pueden interpretar como acuerdos y byc como desacuerdos. El \u00edndice Rand se define como:<\/p>\n<!-- \/wp:paragraph --><!-- wp:image {\"sizeSlug\":\"large\"} -->\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone\" src=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2020\/03\/eval17.png\" alt=\"Criterios de calidad externos (medici\u00f3n basada en informaci\u00f3n mutua, medici\u00f3n de recuperaci\u00f3n de precisi\u00f3n, \u00edndice RAND)\" width=\"222\" height=\"49\" title=\"\"><\/figure>\n<p>Lo que viene con el sistema de calificaci\u00f3n es<\/p>\n<p>(aa+nn)\/NT<\/p>\n<!-- \/wp:image --><!-- wp:paragraph -->\n<p>El \u00edndice Rand est\u00e1 entre 0 y 1. Cuando las dos particiones coinciden perfectamente, el \u00edndice Rand es 1.<\/p>\n<!-- \/wp:paragraph --><!-- wp:paragraph -->\n<p>Un problema con el \u00edndice Rand es que su valor esperado de dos agrupaciones aleatorias no toma un valor constante (como cero). Hubert y Arabia en 1985 sugieren un \u00edndice Rand ajustado que supera este inconveniente.<\/p>\n<!-- \/wp:paragraph -->\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-874a20c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"874a20c\" data-element_type=\"section\" data-e-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-8f88ea6\" data-id=\"8f88ea6\" data-element_type=\"column\" data-e-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-0049040 elementor-widget elementor-widget-heading\" data-id=\"0049040\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Rogers-Tanimoto\"><\/span>Rogers-Tanimoto<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-597d039 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"597d039\" data-element_type=\"section\" data-e-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-29dea5c\" data-id=\"29dea5c\" data-element_type=\"column\" data-e-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-159f296 elementor-widget elementor-widget-text-editor\" data-id=\"159f296\" data-element_type=\"widget\" data-e-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<p>El \u00edndice de Rogers-Tanimoto se define de la siguiente manera:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21141\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Rogers-Tanimoto.png\" alt=\"Rogers-Tanimoto\" width=\"178\" height=\"39\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Rogers-Tanimoto.png 178w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Rogers-Tanimoto-18x4.png 18w\" sizes=\"(max-width: 178px) 100vw, 178px\" \/><\/p>\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-a3215ce elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"a3215ce\" data-element_type=\"section\" data-e-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-001a62c\" data-id=\"001a62c\" data-element_type=\"column\" data-e-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-29f457b elementor-widget elementor-widget-heading\" data-id=\"29f457b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Russel-Rao\"><\/span>Russell Rao<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-b157227 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"b157227\" data-element_type=\"section\" data-e-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-b4102f4\" data-id=\"b4102f4\" data-element_type=\"column\" data-e-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-51c28c6 elementor-widget elementor-widget-text-editor\" data-id=\"51c28c6\" data-element_type=\"widget\" data-e-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<p>El \u00edndice Russell-Rao mide la proporci\u00f3n de coincidencias entre las dos particiones. Se define de la siguiente manera:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21142\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Russel-Rao1.png\" alt=\"Russell Rao\" width=\"57\" height=\"34\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Russel-Rao1.png 57w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Russel-Rao1-18x12.png 18w\" sizes=\"(max-width: 57px) 100vw, 57px\" \/><\/p>\n<p>Este \u00edndice tambi\u00e9n se puede escribir:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21143\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Russel-Rao2.png\" alt=\"Russell Rao\" width=\"207\" height=\"64\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Russel-Rao2.png 207w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Russel-Rao2-18x6.png 18w\" sizes=\"(max-width: 207px) 100vw, 207px\" \/><\/p>\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-da101dd elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"da101dd\" data-element_type=\"section\" data-e-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-e33cbeb\" data-id=\"e33cbeb\" data-element_type=\"column\" data-e-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-3946e81 elementor-widget elementor-widget-heading\" data-id=\"3946e81\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Sokal-Sneath\"><\/span>Sokal-Sneath<span class=\"ez-toc-section-end\"><\/span><\/h2>\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-fde1b86 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"fde1b86\" data-element_type=\"section\" data-e-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-dcb657a\" data-id=\"dcb657a\" data-element_type=\"column\" data-e-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-9d75654 elementor-widget elementor-widget-text-editor\" data-id=\"9d75654\" data-element_type=\"widget\" data-e-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<p>Hay dos versiones del \u00edndice Sokal-Sneath. Se definen respectivamente de la siguiente manera:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21144\" src=\"http:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Sokal-Sneath.png\" alt=\"Sokal-Sneath\" width=\"230\" height=\"89\" title=\"\" srcset=\"https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Sokal-Sneath.png 230w, https:\/\/complex-systems-ai.com\/wp-content\/uploads\/2024\/02\/Sokal-Sneath-18x7.png 18w\" sizes=\"(max-width: 230px) 100vw, 230px\" \/><\/p>\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>","protected":false},"excerpt":{"rendered":"<p>Wiki de partici\u00f3n de datos Inicio Criterios de calidad externos Los \u00edndices de calidad externos son \u00edndices destinados a medir la similitud entre dos... <\/p>","protected":false},"author":1,"featured_media":0,"parent":8271,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-8410","page","type-page","status-publish","hentry"],"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/complex-systems-ai.com\/es\/wp-json\/wp\/v2\/pages\/8410","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/complex-systems-ai.com\/es\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/complex-systems-ai.com\/es\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/complex-systems-ai.com\/es\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/complex-systems-ai.com\/es\/wp-json\/wp\/v2\/comments?post=8410"}],"version-history":[{"count":14,"href":"https:\/\/complex-systems-ai.com\/es\/wp-json\/wp\/v2\/pages\/8410\/revisions"}],"predecessor-version":[{"id":21147,"href":"https:\/\/complex-systems-ai.com\/es\/wp-json\/wp\/v2\/pages\/8410\/revisions\/21147"}],"up":[{"embeddable":true,"href":"https:\/\/complex-systems-ai.com\/es\/wp-json\/wp\/v2\/pages\/8271"}],"wp:attachment":[{"href":"https:\/\/complex-systems-ai.com\/es\/wp-json\/wp\/v2\/media?parent=8410"}],"curies":[{"name":"gracias","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}