{"id":180942,"date":"2024-04-16T19:25:17","date_gmt":"2024-04-16T18:25:17","guid":{"rendered":"https:\/\/datascientest.com\/en\/?p=180942"},"modified":"2024-06-17T13:57:42","modified_gmt":"2024-06-17T12:57:42","slug":"guide-to-modeling-a-machine-learning-project-steps-and-best-practices","status":"publish","type":"post","link":"https:\/\/datascientest.com\/en\/guide-to-modeling-a-machine-learning-project-steps-and-best-practices","title":{"rendered":"Guide to Modeling a Machine Learning Project: Steps and Best Practices"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"180942\" class=\"elementor elementor-180942\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-aec4365 e-flex e-con-boxed e-con\" data-id=\"aec4365\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-35054b3 elementor-widget elementor-widget-heading\" data-id=\"35054b3\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h3 class=\"elementor-heading-title elementor-size-default\">Introduction<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b41f4a8 elementor-widget elementor-widget-text-editor\" data-id=\"b41f4a8\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p>You&#8217;ve probably already <a href=\"https:\/\/datascientest.com\/en\/machine-learning-engineer-bootcamp-why-is-it-interesting\">heard of Machine Learning<\/a> being used to predict the price of a house or in the field of sports betting. It has a wide range of uses, and you&#8217;re probably wondering how it can be used to carry out such a wide variety of projects.<\/p><p>In previous articles, we talked about setting up a suitable environment and exploring the necessary data before starting to <a href=\"https:\/\/datascientest.com\/en\/streamlit-the-tool-for-presenting-your-machine-learning-work\">model a ML project<\/a>. If you haven&#8217;t already read them, we advise you to do so before moving on to modelling.<\/p><p><strong>On today&#8217;s agenda:<\/strong> how to organise the stages involved in modelling the project problem.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-dd4a2db e-flex e-con-boxed e-con\" data-id=\"dd4a2db\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-a8812e3 e-con-full e-flex e-con\" data-id=\"a8812e3\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-609a4a2 e-con-full e-flex e-con\" data-id=\"609a4a2\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-cdefba0 elementor-widget elementor-widget-video\" data-id=\"cdefba0\" data-element_type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/youtu.be\\\/FeirpwB2HWQ?si=kUBe1-lucsFUVWQJ&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-video .elementor-widget-container{overflow:hidden;transform:translateZ(0)}.elementor-widget-video .elementor-wrapper{aspect-ratio:var(--video-aspect-ratio)}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{height:100%;width:100%;display:flex;border:none;background-color:#000}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-wrapper{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .elementor-open-inline .elementor-custom-embed-image-overlay{position:absolute;top:0;right:0;bottom:0;left:0;background-size:cover;background-position:50%}.elementor-widget-video .elementor-custom-embed-image-overlay{cursor:pointer;text-align:center}.elementor-widget-video .elementor-custom-embed-image-overlay:hover .elementor-custom-embed-play i{opacity:1}.elementor-widget-video .elementor-custom-embed-image-overlay img{display:block;width:100%;aspect-ratio:var(--video-aspect-ratio);-o-object-fit:cover;object-fit:cover;-o-object-position:center center;object-position:center center}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-custom-embed-image-overlay{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-custom-embed-image-overlay img{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .e-hosted-video .elementor-video{-o-object-fit:cover;object-fit:cover}.e-con-inner>.elementor-widget-video,.e-con>.elementor-widget-video{width:var(--container-widget-width);--flex-grow:var(--container-widget-flex-grow)}<\/style>\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f2abf2b elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"f2abf2b\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/en\/machine-learning-engineer-course\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Discover our Machine Learning Engineer Training<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-d4b5cdd e-con-full e-flex e-con\" data-id=\"d4b5cdd\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-c699ca5 e-flex e-con-boxed e-con\" data-id=\"c699ca5\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-cf13c1d elementor-widget elementor-widget-heading\" data-id=\"cf13c1d\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Model selection<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b8a82c9 elementor-widget elementor-widget-text-editor\" data-id=\"b8a82c9\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>If you have followed the steps in the previous article, your dataset and production environment should be ready for modelling.<\/p><p>Let&#8217;s start by modelling the problem, i.e. transforming the problem into a particular task.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1d8c9f1 elementor-widget elementor-widget-heading\" data-id=\"1d8c9f1\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h5 class=\"elementor-heading-title elementor-size-default\">Types of learning<\/h5>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-47c372e elementor-widget elementor-widget-text-editor\" data-id=\"47c372e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>We distinguish<a href=\"https:\/\/datascientest.com\/en\/automl-and-machine-learning-automation-a-threat-to-data-scientists\"> two main families in the ML field:<\/a> supervised and <a href=\"https:\/\/datascientest.com\/en\/unsupervised-learning-principle-and-use\">unsupervised learning.<\/a><\/p><p><strong>Note:<\/strong> There are also other types of learning, such as semi-supervised learning and <strong>reinforcement learning,<\/strong> which we will not explore in this article.<\/p><p>The question to ask yourself to determine which family your problem belongs to is the following: <em>Do you have the target variable for my project?<\/em><\/p><p>Your target variable is the column you are trying to predict. If you have the values for this column, you are in<strong> supervised learning.<\/strong><\/p><p>If, on the other hand, you are trying to obtain an estimate of this column without having the exact values, you are in unsupervised learning.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4f92c2e elementor-widget elementor-widget-heading\" data-id=\"4f92c2e\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h6 class=\"elementor-heading-title elementor-size-default\"><b>1) Unsupervised learning<\/b>.<\/h6>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-71ee208 elementor-widget elementor-widget-text-editor\" data-id=\"71ee208\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>In the case of unsupervised learning, you will need to use the <strong>following techniques:<\/strong><\/p><ul><li>Clustering (<a href=\"https:\/\/datascientest.com\/en\/k-means-clustering-in-machine-learning-a-deep-dive\">Kmeans<\/a>, <a href=\"https:\/\/datascientest.com\/en\/meanshift-everything-you-need-to-know-about-the-data-clustering-algorithm\">MeanShift,<\/a> <a href=\"https:\/\/datascientest.com\/en\/spectral-clustering-definition-operation-use\">Spectral Clustering<\/a>, etc.)<\/li><li><strong>Dimension reduction algorithms<\/strong> (PCA, TSNE)<\/li><li>Anomaly detection (EllipticEnvelope, IsolationForest)<\/li><\/ul><p>Need to brush up on these topics? They&#8217;re all covered on our blog.<\/p><p>Let&#8217;s move on to supervised learning.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b936183 elementor-widget elementor-widget-heading\" data-id=\"b936183\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h6 class=\"elementor-heading-title elementor-size-default\"><b>2) Supervised learning<\/b>.<\/h6>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-54e56bd elementor-widget elementor-widget-text-editor\" data-id=\"54e56bd\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>If, on the other hand, your<a href=\"https:\/\/datascientest.com\/en\/datasets-top-5-places-to-find-quality-datasets\"> dataset<\/a> contains the target variable, you need to ask yourself whether the column you are trying to predict is a continuous or categorical variable.<\/p><p>A continuous variable is, for example, the price of a house or the time a person spends on a site before making a purchase.<\/p><p>A categorical variable, on the other hand, has a finite and restricted number of modalities, such as an age group or the different types of loyalty subscription offered by a particular telephone company.<\/p><p>There are many<a href=\"https:\/\/datascientest.com\/en\/calculate-correlation-between-two-variables-how-do-you-measure-dependence\"> different regression algorithms.<\/a> These include linear regression, random forests and SVM regression.<\/p><p>There are also many classification algorithms, such as decision trees or the <a href=\"https:\/\/datascientest.com\/en\/svm-support-vector-machines-unveiled-understanding-implementation-significance\">SVM model.<\/a><\/p><p>Once again, don&#8217;t panic, if you feel that a refresher on these algo&#8217;s would be useful, we have dedicated an article to them on the blog that we invite you to have a look at.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f018c43 elementor-widget elementor-widget-text-editor\" data-id=\"f018c43\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Display<strong> supervised or unsupervised learning?<\/strong><\/p><p>In both cases, there is no magic formula. You need to test the different models to determine which will give you the best performance.<\/p><p>However, if you are using a classification model and your classes are unbalanced, it is advisable to rebalance your dataset using resampling techniques.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8b72ee5 elementor-widget elementor-widget-image\" data-id=\"8b72ee5\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/10\/image4.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\"><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8c5919b elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"8c5919b\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\/data-courses\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Discover our courses<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6198a43 elementor-widget elementor-widget-text-editor\" data-id=\"6198a43\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Deep models and <a href=\"https:\/\/datascientest.com\/en\/deep-neural-network-what-is-it-and-how-is-it-working\">neural networks<\/a> can also be used for both regression and classification. Often, they will give you higher performance, but they have two disadvantages that need to be taken into account.<\/p><p>Neural networks are very prone to overlearning (i.e. they are difficult to generalise) and are not very interpretable. What we mean by interpretable is that it is complex to understand and anticipate their decisions.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-ee828f6 e-flex e-con-boxed e-con\" data-id=\"ee828f6\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-637340d elementor-widget elementor-widget-menu-anchor\" data-id=\"637340d\" data-element_type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\nbody.elementor-page .elementor-widget-menu-anchor{margin-bottom:0}<\/style>\t\t<div id=\"selection\" class=\"elementor-menu-anchor\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-de37a48 elementor-widget elementor-widget-heading\" data-id=\"de37a48\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Model selection and optimisation<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-83a2087 elementor-widget elementor-widget-text-editor\" data-id=\"83a2087\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>You now have the performance of each of the models that could be applied to your problem. <em>Now you need to select the best performing model, but how?<\/em><\/p><p><a href=\"https:\/\/datascientest.com\/en\/the-importance-of-cross-validation\">Cross-validation<\/a> is a very useful technique that lets you know whether your model is generalizable: in other words, whether it behaves well when it encounters new data.<\/p><p>It also allows you to find the optimal hyper-parameters of your model in parallel with the optimisation method. There are several methods for optimising hyper-parameters, such as the `GridSearchCV` function, random search or <a href=\"https:\/\/datascientest.com\/en\/bayesian-optimization-definition-and-operation\">Bayesian optimisation&#8230;<\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-8f67b29 e-flex e-con-boxed e-con\" data-id=\"8f67b29\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-fb4fa85 elementor-widget elementor-widget-menu-anchor\" data-id=\"fb4fa85\" data-element_type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div id=\"metrique\" class=\"elementor-menu-anchor\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3e8b6cf elementor-widget elementor-widget-heading\" data-id=\"3e8b6cf\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Metric<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-57c4bf7 e-flex e-con-boxed e-con\" data-id=\"57c4bf7\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-3b3e068 e-con-full e-flex e-con\" data-id=\"3b3e068\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-42df7d7 elementor-widget elementor-widget-text-editor\" data-id=\"42df7d7\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Obtaining the performance of tuning models, but according to which metric?<\/p><p>For regression problems, you can consider the MAE, MSE or R2 metrics.<\/p><p>For <a href=\"https:\/\/datascientest.com\/en\/classification-algorithms-definition-and-main-models\">classification problems,<\/a> you can use the confusion matrix or classification report tools.<\/p><p>The confusion matrix is a practical representation of the precision of a model with two or more classes, while the classification report will give you more information about other measures (such as recall, f1 score, etc.).<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-8cbd65e e-con-full e-flex e-con\" data-id=\"8cbd65e\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t<div class=\"elementor-element elementor-element-27d137d e-flex e-con-boxed e-con\" data-id=\"27d137d\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-8322aa5 elementor-widget elementor-widget-image\" data-id=\"8322aa5\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/10\/image2-1.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\"><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-7024c9a e-flex e-con-boxed e-con\" data-id=\"7024c9a\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4e8af17 elementor-widget elementor-widget-image\" data-id=\"4e8af17\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/10\/image3.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\"><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-95e3715 e-flex e-con-boxed e-con\" data-id=\"95e3715\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7f70914 elementor-widget elementor-widget-image\" data-id=\"7f70914\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/10\/image1-1.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-48a5335 e-flex e-con-boxed e-con\" data-id=\"48a5335\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-19cb6cd elementor-widget elementor-widget-image\" data-id=\"19cb6cd\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/10\/image5-2.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\"><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-6cbe92a e-flex e-con-boxed e-con\" data-id=\"6cbe92a\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-57c8a96 elementor-widget elementor-widget-heading\" data-id=\"57c8a96\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Finalisation<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6f9c27e elementor-widget elementor-widget-text-editor\" data-id=\"6f9c27e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>At this stage, you have the performance of your different models on your dataset with the optimal hyper-parameters, as well as the evaluation metric(s). You can now compare their performance and agree on the best model.<\/p><p>To do this, you need to consider not only the model&#8217;s performance, but also its interpretability. In certain fields, such as medicine or autonomous driving, it can be crucial to understand how your model makes its decisions. So you need to take these two concepts into account to find the best compromise and agree on the most appropriate model.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-01171d5 e-flex e-con-boxed e-con\" data-id=\"01171d5\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-08f278f elementor-widget elementor-widget-heading\" data-id=\"08f278f\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Conclusion<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a5a8b10 elementor-widget elementor-widget-text-editor\" data-id=\"a5a8b10\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Now you know how to carry out the various modelling stages of your project.<\/p><p>If you liked this article or the others, don&#8217;t forget to subscribe to our YouTube channel to be alerted to Data Science topics that might interest you.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-68de065 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"68de065\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\/data-courses\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Discover our courses<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Introduction You&#8217;ve probably already heard of Machine Learning being used to predict the price of a house or in the field of sports betting. It has a wide range of uses, and you&#8217;re probably wondering how it can be used to carry out such a wide variety of projects. In previous articles, we talked about [&hellip;]<\/p>\n","protected":false},"author":67,"featured_media":18442,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2409],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Guide to Modeling a Machine Learning Project: Steps and Best Practices<\/title>\n<meta name=\"description\" content=\"Learn about the essential steps and best practices involved in modeling a machine learning project, including data preprocessing, model selection, hyperparameter tuning, evaluation metrics, and deployment considerations.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datascientest.com\/en\/guide-to-modeling-a-machine-learning-project-steps-and-best-practices\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Guide to Modeling a Machine Learning Project: Steps and Best Practices\" \/>\n<meta property=\"og:description\" content=\"Introduction You&#039;ve probably already heard of Machine Learning being used to predict the price of a house or in the field of sports betting. 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