{"id":5126,"date":"2021-06-21T15:34:52","date_gmt":"2021-06-21T13:34:52","guid":{"rendered":"https:\/\/dev.m2hycon.de\/aktuelles\/unkategorisiert\/deep-lattice-networks-dln\/"},"modified":"2024-05-15T17:00:55","modified_gmt":"2024-05-15T15:00:55","slug":"deep-lattice-networks-dln","status":"publish","type":"post","link":"https:\/\/www.m2hycon.de\/en\/news\/practice\/deep-lattice-networks-dln\/","title":{"rendered":"Deep Lattice Networks (DLN)"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"5126\" class=\"elementor elementor-5126 elementor-4186\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-ff85573 elementor-section-full_width elementor-section-height-min-height red noisy elementor-section-height-default elementor-section-items-middle\" data-id=\"ff85573\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-482e998\" data-id=\"482e998\" 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-a820fea elementor-widget elementor-widget-theme-post-featured-image elementor-widget-image\" data-id=\"a820fea\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"theme-post-featured-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=\"1024\" height=\"512\" src=\"https:\/\/www.m2hycon.de\/wp-content\/uploads\/2023\/02\/m2hycon_blog_deep_lattice_1920x960-1024x512.jpg\" class=\"attachment-large size-large wp-image-4966\" alt srcset=\"https:\/\/www.m2hycon.de\/wp-content\/uploads\/2023\/02\/m2hycon_blog_deep_lattice_1920x960-1024x512.jpg 1024w, https:\/\/www.m2hycon.de\/wp-content\/uploads\/2023\/02\/m2hycon_blog_deep_lattice_1920x960-300x150.jpg 300w, https:\/\/www.m2hycon.de\/wp-content\/uploads\/2023\/02\/m2hycon_blog_deep_lattice_1920x960-768x384.jpg 768w, https:\/\/www.m2hycon.de\/wp-content\/uploads\/2023\/02\/m2hycon_blog_deep_lattice_1920x960-1536x768.jpg 1536w, https:\/\/www.m2hycon.de\/wp-content\/uploads\/2023\/02\/m2hycon_blog_deep_lattice_1920x960.jpg 1920w\" 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-8c2be4e elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"8c2be4e\" 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-923e421\" data-id=\"923e421\" 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-7118ddc elementor-widget elementor-widget-theme-post-title elementor-page-title elementor-widget-heading\" data-id=\"7118ddc\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"theme-post-title.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">Deep Lattice Networks (DLN)<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b319741 elementor-widget elementor-widget-post-info\" data-id=\"b319741\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"post-info.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-inline-items elementor-icon-list-items elementor-post-info\">\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item elementor-repeater-item-20ff1f2 elementor-inline-item\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text elementor-post-info__item elementor-post-info__item--type-custom\">\n\t\t\t\t\t\t\t\t\t\tVon Bj\u00f6rn Piepen\u00adburg\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t<li class=\"elementor-icon-list-item elementor-repeater-item-2efc209 elementor-inline-item\" itemprop=\"datePublished\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text elementor-post-info__item elementor-post-info__item--type-date\">\n\t\t\t\t\t\t\t\t\t\t<time>June 21, 2021<\/time>\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t<li class=\"elementor-icon-list-item elementor-repeater-item-84e7708 elementor-inline-item\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text elementor-post-info__item elementor-post-info__item--type-custom\">\n\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.m2hycon.de\/en\/tag\/binary\/\" rel=\"tag\">binary<\/a>, <a href=\"https:\/\/www.m2hycon.de\/en\/tag\/classification\/\" rel=\"tag\">Classi\u00adfi\u00adca\u00adtion<\/a>, <a href=\"https:\/\/www.m2hycon.de\/en\/tag\/deep-lattice-network\/\" rel=\"tag\">Deep lattice network<\/a>, <a href=\"https:\/\/www.m2hycon.de\/en\/tag\/monotony\/\" rel=\"tag\">Monotony<\/a>, <a href=\"https:\/\/www.m2hycon.de\/en\/tag\/tensorflow-en\/\" rel=\"tag\">Tensor\u00adflow<\/a>\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-f9ac5b0 elementor-section-content-middle elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f9ac5b0\" 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-inner-column elementor-element elementor-element-c38a12e\" data-id=\"c38a12e\" 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-5c8e1ed elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"5c8e1ed\" 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<h4>Share post:<\/h4>\n\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-ae685d9 elementor-share-buttons--view-icon elementor-share-buttons--skin-minimal elementor-share-buttons--color-custom elementor-widget__width-auto elementor-share-buttons--shape-circle elementor-grid-0 elementor-widget elementor-widget-share-buttons\" data-id=\"ae685d9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"share-buttons.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-grid\" role=\"list\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-grid-item\" role=\"listitem\">\n\t\t\t\t\t\t<div class=\"elementor-share-btn elementor-share-btn_facebook\" role=\"button\" tabindex=\"0\" aria-label=\"Share on facebook\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-share-btn__icon\">\n\t\t\t\t\t\t\t\t<i class=\"fab fa-facebook\" aria-hidden=\"true\"><\/i>\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-grid-item\" role=\"listitem\">\n\t\t\t\t\t\t<div class=\"elementor-share-btn elementor-share-btn_twitter\" role=\"button\" tabindex=\"0\" aria-label=\"Share on twitter\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-share-btn__icon\">\n\t\t\t\t\t\t\t\t<i class=\"fab fa-twitter\" aria-hidden=\"true\"><\/i>\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-grid-item\" role=\"listitem\">\n\t\t\t\t\t\t<div class=\"elementor-share-btn elementor-share-btn_linkedin\" role=\"button\" tabindex=\"0\" aria-label=\"Share on linkedin\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-share-btn__icon\">\n\t\t\t\t\t\t\t\t<i class=\"fab fa-linkedin\" aria-hidden=\"true\"><\/i>\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-grid-item\" role=\"listitem\">\n\t\t\t\t\t\t<div class=\"elementor-share-btn elementor-share-btn_xing\" role=\"button\" tabindex=\"0\" aria-label=\"Share on xing\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-share-btn__icon\">\n\t\t\t\t\t\t\t\t<i class=\"fab fa-xing\" aria-hidden=\"true\"><\/i>\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\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\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-f408ab5 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f408ab5\" 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-281546f\" data-id=\"281546f\" 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-d986110 math elementor-widget elementor-widget-text-editor\" data-id=\"d986110\" 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>Frequent problems that we are confronted with can be traced back to a (multi\u00addi\u00admen\u00adsional) regres\u00adsion or a classi\u00adfi\u00adca\u00adtion. Starting from a set of charac\u00adte\u00adristics, regres\u00adsion attempts to repre\u00adsent the depen\u00addency between the charac\u00adte\u00adristics and a target variable as a function. One example would be the depen\u00addence of turnover on expen\u00additure on research and on employee satis\u00adfac\u00adtion in a company. Classi\u00adfi\u00adca\u00adtion involves estimating the proba\u00adbi\u00adlity that an object belongs to a prede\u00adfined class. A well-known example is the classi\u00adfi\u00adca\u00adtion of image content (dog, cat, truck, \u2026).<\/p>\n<p>The comple\u00adxity of regres\u00adsion and classi\u00adfi\u00adca\u00adtion problems depends on the number of features and the degree of corre\u00adla\u00adtion between the features and the target variable. Another aspect is the inter\u00adde\u00adpen\u00addence of the charac\u00adte\u00adristics. Simple problems can be solved using classical static methods, which have the advan\u00adtage that the results can be easily inter\u00adpreted. Problems of practical relevance are generally described by several charac\u00adte\u00adristics that influence each other. A well-known and frequently used method for solving such problems is an artifi\u00adcial neural network, which is very powerful in solving these problems.<\/p>\n<p><em>Deep lattice networks<\/em> extend the proper\u00adties of an artifi\u00adcial neural network to include <em>monoto\u00adni\u00adcity condi\u00adtions<\/em> between indivi\u00addual features and the target variable. One example of the neces\u00adsity of this is a price model in which the price of a unit is to be reduced with the order quantity. The project, which was initiated and supported by  <em>Google<\/em>  developed process consists essen\u00adti\u00adally of  <span class=\"katex\"><span class=\"katex-mathml\">n<\/span><span class=\"katex-html\" aria-hidden=\"true\"><br>\n  <span class=\"base\"><br>\n    <span class=\"mord mathnormal\">n<\/span><br>\n  <\/span><br>\n<\/span><\/span>-dimen\u00adsional  <em>Hyper\u00adcube<\/em>  the edge length  <span class=\"katex\"><span class=\"katex-mathml\">1<\/span><span class=\"katex-html\" aria-hidden=\"true\"><br>\n  <span class=\"base\"><br>\n    <span class=\"mord\">1<\/span><br>\n  <\/span><br>\n<\/span><\/span>where  <span class=\"katex\"><span class=\"katex-mathml\">n<\/span><span class=\"katex-html\" aria-hidden=\"true\"><br>\n  <span class=\"base\"><br>\n    <span class=\"mord mathnormal\">n<\/span><br>\n  <\/span><br>\n<\/span><\/span>  describes the number of charac\u00adte\u00adristics. Each dimen\u00adsion of the cube there\u00adfore repres\u00adents a charac\u00adte\u00adristic. A (multi\u00addi\u00admen\u00adsional) function is placed in the cube, which describes the relati\u00adonship between the charac\u00adte\u00adristics and the target variable. For this purpose, function values are calcu\u00adlated for the corner points of the cube, which repre\u00adsent the variable parame\u00adters of the model, on the basis of training data. The target function is inter\u00adpo\u00adlated linearly between the corner points. The edges of the cube can be subdi\u00advided to increase the detail of the function. A <em>grid<\/em><em>(lattice<\/em>) is placed through the division points, the inter\u00adsec\u00adtion points of which are assigned function values as additional parame\u00adters of the model.<\/p>\n<p>The follo\u00adwing figure shows a lattice with two features (i.e. a square). For the four corner points <span class=\"katex\"><br>\n  <span class=\"katex-mathml\">\u03b8[i]<\/span><br>\n  <span class=\"katex-html\" aria-hidden=\"true\"><br>\n    <span class=\"base\"><br>\n      <span class=\"mord mathnormal\">\u03b8<\/span><br>\n      <span class=\"mopen\">[<\/span><br>\n      <span class=\"mord mathnormal\">i<\/span><br>\n      <span class=\"mclose\">]<\/span><br>\n    <\/span><br>\n  <\/span><br>\n<\/span> values were derived from a set of training data as parame\u00adters of the model. The function to be repre\u00adsented <span class=\"katex\"><br>\n  <span class=\"katex-mathml\">f(x)<\/span><br>\n  <span class=\"katex-html\" aria-hidden=\"true\"><br>\n    <span class=\"base\"><br>\n      <span class=\"mord mathnormal\">f<\/span><br>\n      <span class=\"mopen\">(<\/span><br>\n      <span class=\"mord mathnormal\">x<\/span><br>\n      <span class=\"mclose\">)<\/span><br>\n    <\/span><br>\n  <\/span><br>\n<\/span> is appro\u00adxi\u00admated by linear inter\u00adpo\u00adla\u00adtion between the four corner points. No further support points were used between the corner points to compress the grid and increase the level of detail of the appro\u00adxi\u00admated function.<\/p>\n\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-1e5efd4 elementor-widget elementor-widget-image\" data-id=\"1e5efd4\" data-element_type=\"widget\" data-e-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.m2hycon.de\/wp-content\/uploads\/elementor\/thumbs\/m2hycon_blog_deep_lattice_in_text_1920x960-q1uxbwb72ihr2v3zmidh3c9u981oargg58besbjlj8.jpg\" title=\"Deep Lattice Netzwerke (DLN)\" alt=\"Deep Lattice Netzwerke (DLN)\" 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-6f2957d math elementor-widget elementor-widget-text-editor\" data-id=\"6f2957d\" 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\tWith an increase in the number of features or by incre\u00adasing the level of detail  \nof the function to be repre\u00adsented, the number of functions to be optimized increases.  \nparameter exponen\u00adti\u00adally. Let\u2019s take an example: you have <span>\n  <span class=\"katex\">\n    <span class=\"katex-mathml\">\n      <math>\n        <semantics>\n          <mrow>\n            <mn>15<\/mn>\n          <\/mrow>\n        <\/semantics>\n      <\/math>\n    <\/span>\n    <span class=\"katex-html\" aria-hidden=\"true\">\n      <span class=\"base\">\n        <span class=\"strut\" style=\"height: 0.64444em; vertical-align: 0em;\"><\/span>\n        <span class=\"mord\">15<\/span>\n      <\/span>\n    <\/span>\n  <\/span>\n<\/span> charac\u00adte\u00adristics that have an influence on the target value. Each charac\u00adte\u00adristic should be charac\u00adte\u00adrized by  <span><span class=\"katex\"><span class=\"katex-mathml\">\n  <math>\n    <semantics>\n      <mrow>\n        <mn>10<\/mn>\n      <\/mrow>\n    <\/semantics>\n  <\/math>\n<\/span><span class=\"katex-html\" aria-hidden=\"true\">\n  <span class=\"base\">\n    <span class=\"strut\" style=\"height: 0.64444em; vertical-align: 0em;\"><\/span>\n    <span class=\"mord\">10<\/span>\n  <\/span>\n<\/span><\/span><\/span>  Support points (<span><span class=\"katex\"><span class=\"katex-mathml\">\n  <math>\n    <semantics>\n      <mrow>\n        <mn>2<\/mn>\n      <\/mrow>\n    <\/semantics>\n  <\/math>\n<\/span><span class=\"katex-html\" aria-hidden=\"true\">\n  <span class=\"base\">\n    <span class=\"strut\" style=\"height: 0.64444em; vertical-align: 0em;\"><\/span>\n    <span class=\"mord\">2<\/span>\n  <\/span>\n<\/span><\/span><\/span>  Key points and  <span><span class=\"katex\"><span class=\"katex-mathml\">\n  <math>\n    <semantics>\n      <mrow>\n        <mn>8<\/mn>\n      <\/mrow>\n    <\/semantics>\n  <\/math>\n<\/span><span class=\"katex-html\" aria-hidden=\"true\">\n  <span class=\"base\">\n    <span class=\"strut\" style=\"height: 0.64444em; vertical-align: 0em;\"><\/span>\n    <span class=\"mord\">8<\/span>\n  <\/span>\n<\/span><\/span><\/span>  additional subdi\u00advi\u00adsion points) can be described in the lattice. This creates a cube with  <span><span class=\"katex\"><span class=\"katex-mathml\"><math><semantics><mrow><mn>1<\/mn><msup><mn>0<\/mn><mn>15<\/mn><\/msup><mo>=<\/mo><mn>1<\/mn><\/mrow><\/semantics><\/math><\/span><span class=\"katex-html\" aria-hidden=\"true\"><span class=\"base\"><span class=\"strut\" style=\"height: 0.814108em; vertical-align: 0em;\"><\/span><span class=\"mord\">1<\/span><span class=\"mord\">\n  <span class=\"mord\">0<\/span>\n  <span class=\"msupsub\">\n    <span class=\"vlist-t\">\n      <span class=\"vlist-r\">\n        <span class=\"vlist\" style=\"height: 0.814108em;\">\n          <span class style=\"top: -3.063em; margin-right: 0.05em;\">\n            <span class=\"pstrut\" style=\"height: 2.7em;\"><\/span>\n            <span class=\"sizing reset-size6 size3 mtight\">\n              <span class=\"mord mtight\">\n                <span class=\"mord mtight\">15<\/span>\n              <\/span>\n            <\/span>\n          <\/span>\n        <\/span>\n      <\/span>\n    <\/span>\n  <\/span>\n<\/span><span class=\"mspace\" style=\"margin-right: 0.277778em;\"><\/span><span class=\"mrel\">=<\/span><span class=\"mspace\" style=\"margin-right: 0.277778em;\"><\/span><\/span><span class=\"base\"><span class=\"strut\" style=\"height: 0.64444em; vertical-align: 0em;\"><\/span><span class=\"mord\">1<\/span><\/span><\/span><\/span><\/span>\n  quadril\u00adlion variable parame\u00adters. To reduce the comple\u00adxity of the  \nmodel, the charac\u00adte\u00adristics can be divided into several separate  \ndice, the results of which are combined after the training sessions.  \nbecome. The so-called Crystal algorithm can be used to deter\u00admine the\n  Charac\u00adte\u00adristics accor\u00adding to their simila\u00adrity on diffe\u00adrent cubes  \nto divide. Merging can be done via a simple  \naveraging or through further lattices, whereby a  \nLattice network is created.\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-9ff84e4 elementor-widget elementor-widget-image\" data-id=\"9ff84e4\" data-element_type=\"widget\" data-e-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=\"768\" height=\"268\" src=\"https:\/\/www.m2hycon.de\/wp-content\/uploads\/2023\/02\/m2hycon_blog_deep_lattice_in_text_1384\u200a\u00d7\u200a483-768x268.jpg\" class=\"attachment-medium_large size-medium_large wp-image-4969\" alt srcset=\"https:\/\/www.m2hycon.de\/wp-content\/uploads\/2023\/02\/m2hycon_blog_deep_lattice_in_text_1384\u200a\u00d7\u200a483-768x268.jpg 768w, https:\/\/www.m2hycon.de\/wp-content\/uploads\/2023\/02\/m2hycon_blog_deep_lattice_in_text_1384\u200a\u00d7\u200a483-300x105.jpg 300w, https:\/\/www.m2hycon.de\/wp-content\/uploads\/2023\/02\/m2hycon_blog_deep_lattice_in_text_1384\u200a\u00d7\u200a483-1024x357.jpg 1024w, https:\/\/www.m2hycon.de\/wp-content\/uploads\/2023\/02\/m2hycon_blog_deep_lattice_in_text_1384\u200a\u00d7\u200a483.jpg 1384w\" 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-c77b021 math elementor-widget elementor-widget-text-editor\" data-id=\"c77b021\" 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>Similar to an artifi\u00adcial neural network, training is performed by itera\u00adtively adjus\u00adting the parame\u00adters with the aim of minimi\u00adzing the error between the model output and the observed values of the target variable. This proce\u00addure is known as super\u00advised learning. After training, values for the target variable can be deter\u00admined for (unknown) feature combi\u00adna\u00adtions. <span style=\"text-decoration: underline;\"><br>\n  <strong><br>\n    <a href=\"https:\/\/www.m2hycon.de\/en\/news\/practice\/estimation-of-a-customer-specific-offer-acceptance-probability\/\">In another post in this blog<\/a><br>\n  <\/strong><br>\n<\/span> I describe the appli\u00adca\u00adtion of a deep lattice network to deter\u00admine the accep\u00adtance proba\u00adbi\u00adli\u00adties for trans\u00adpor\u00adta\u00adtion orders. This is part of a research project funded by the mFund, which we have successfully imple\u00admented.<\/p>\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-c519333 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"c519333\" 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-50 elementor-top-column elementor-element elementor-element-ac9195e\" data-id=\"ac9195e\" 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-b592d10 elementor-widget elementor-widget-author-box\" data-id=\"b592d10\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"author-box.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-author-box\">\n\t\t\t\t\t\t\t<div class=\"elementor-author-box__avatar\">\n\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.m2hycon.de\/wp-content\/uploads\/2023\/09\/m2hycon_ueberuns_team_Bjoern_Piepenburg_800x800-300x300.jpg\" alt=\"Picture of Bj\u00f6rn Piepenburg\" loading=\"lazy\">\n\t\t\t\t<\/div>\n\t\t\t\n\t\t\t<div class=\"elementor-author-box__text\">\n\t\t\t\t\t\t\t\t\t<div>\n\t\t\t\t\t\t<h4 class=\"elementor-author-box__name\">\n\t\t\t\t\t\t\tBj\u00f6rn Piepen\u00adburg\t\t\t\t\t\t<\/h4>\n\t\t\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\t\t<\/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<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-4ee3c0b elementor-hidden-tablet elementor-hidden-mobile\" data-id=\"4ee3c0b\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\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-ead50ba elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"ead50ba\" 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-94af29a\" data-id=\"94af29a\" 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-de64447 elementor-widget elementor-widget-post-navigation\" data-id=\"de64447\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"post-navigation.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-post-navigation\" role=\"navigation\" aria-label=\"Post Navigation\">\n\t\t\t<div class=\"elementor-post-navigation__prev elementor-post-navigation__link\">\n\t\t\t\t<a href=\"https:\/\/www.m2hycon.de\/en\/news\/wiki\/bayesian-statistics-as-an-extension-of-machine-learning-methods\/\" rel=\"prev\"><span class=\"post-navigation__arrow-wrapper post-navigation__arrow-prev\"><i aria-hidden=\"true\" class=\"fas fa-angle-left\"><\/i><span class=\"elementor-screen-only\">Prev<\/span><\/span><span class=\"elementor-post-navigation__link__prev\"><span class=\"post-navigation__prev--label\">Previous post<\/span><span class=\"post-navigation__prev--title\">Bayesian statis\u00adtics as an exten\u00adsion of machine learning methods<\/span><\/span><\/a>\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"elementor-post-navigation__next elementor-post-navigation__link\">\n\t\t\t\t<a href=\"https:\/\/www.m2hycon.de\/en\/news\/practice\/new-publication-in-the-trade-magazine-digitale-welt\/\" rel=\"next\"><span class=\"elementor-post-navigation__link__next\"><span class=\"post-navigation__next--label\">Next post<\/span><span class=\"post-navigation__next--title\">New publi\u00adca\u00adtion in the trade magazine \u201cDigitale Welt\u201d<\/span><\/span><span class=\"post-navigation__arrow-wrapper post-navigation__arrow-next\"><i aria-hidden=\"true\" class=\"fas fa-angle-right\"><\/i><span class=\"elementor-screen-only\">Next<\/span><\/span><\/a>\t\t\t<\/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<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Frequent problems that we are confronted with can be traced back to a (multi\u00addi\u00admen\u00adsional) regres\u00adsion or a classi\u00adfi\u00adca\u00adtion. Starting from a set of charac\u00adte\u00adristics, regres\u00adsion attempts to repre\u00adsent the depen\u00addency between the charac\u00adte\u00adristics and a target variable as a function.<\/p>\n","protected":false},"author":11,"featured_media":4966,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"elementor_theme","format":"standard","meta":{"wp_typography_post_enhancements_disabled":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"disabled","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"disabled","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[165,172],"tags":[192,191,185,193,194],"class_list":["post-5126","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-practice","category-technology-trends","tag-binary","tag-classification","tag-deep-lattice-network","tag-monotony","tag-tensorflow-en"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.5 (Yoast SEO v28.5) - 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