{"id":18099,"date":"2021-06-08T10:06:21","date_gmt":"2021-06-08T04:36:21","guid":{"rendered":"http:\/\/www.fusioncharts.com\/blog\/?p=18099"},"modified":"2026-01-20T14:41:14","modified_gmt":"2026-01-20T09:11:14","slug":"powerful-multi-series-charts-can-visualize-machine-learning-regression-data","status":"publish","type":"post","link":"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/","title":{"rendered":"Interactive Multi-Series Charts for Regression Analysis 2026"},"content":{"rendered":"<span data-preserver-spaces=\"true\">A challenging problem in machine learning and data science is that of regression analysis. Regression analysis is about finding a suitable model to estimate the relationship between two or more variables. The final model predicts a variable, also called the outcome variable, from the value of one or more predictor variables. Therefore, <\/span><a class=\"editor-rtfLink\" href=\"https:\/\/www.fusioncharts.com\" target=\"_blank\" rel=\"noopener noreferrer\"><span data-preserver-spaces=\"true\">FusionCharts<\/span><\/a><span data-preserver-spaces=\"true\">\u00a0provides an easy method for adding multi-series charts to your web and mobile apps to aid regression analysis.<\/span>\r\n\r\n<span data-preserver-spaces=\"true\">For all regression problems, the first step is to visualize the relationship between the outcome variable and the predictors. Automated tools for creating plots, <a href=\"https:\/\/www.fusioncharts.com\/charts\/realtime-charts\">live charts<\/a>, and maps are of paramount importance to the machine learning and data science community. <\/span><a class=\"editor-rtfLink\" href=\"https:\/\/www.fusioncharts.com\" target=\"_blank\" rel=\"noopener noreferrer\"><span data-preserver-spaces=\"true\">FusionCharts<\/span><\/a><span data-preserver-spaces=\"true\">\u00a0has provided an extensive library of 100+ 2000+ maps to create stunning and powerful interactive visualizations.<\/span>\r\n\r\n<span data-preserver-spaces=\"true\">Read on to find out how you can create an app to generate the multi-series chart of the well-known\u00a0<\/span><a class=\"editor-rtfLink\" href=\"https:\/\/archive.ics.uci.edu\/ml\/datasets\/auto+mpg\" target=\"_blank\" rel=\"noopener noreferrer\"><span data-preserver-spaces=\"true\">auto-mpg regression dataset<\/span><\/a><span data-preserver-spaces=\"true\">\u00a0provided by the\u00a0<\/span><a class=\"editor-rtfLink\" href=\"https:\/\/archive.ics.uci.edu\/ml\/index.php\" target=\"_blank\" rel=\"noopener noreferrer\"><span data-preserver-spaces=\"true\">UCI Machine Learning Repository<\/span><\/a><span data-preserver-spaces=\"true\">.<\/span>\r\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_71 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\"><p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<\/div><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:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#About_the_Auto-mpg_Dataset\" title=\"About the Auto-mpg Dataset\">About the Auto-mpg Dataset<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#The_Multi-Series_Chart\" title=\"The Multi-Series Chart\">The Multi-Series Chart<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#Step_1_Setup_the_Webpack_Project\" title=\"Step 1: Setup the Webpack Project\">Step 1: Setup the Webpack Project<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#Step_11_Install_Webpack_and_FusionCharts\" title=\"Step 1.1: Install Webpack and FusionCharts\">Step 1.1: Install Webpack and FusionCharts<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#Step_12_Make_srcdist_Directories_and_Create_indexjs\" title=\"Step 1.2: Make src+dist Directories and Create index.js\">Step 1.2: Make src+dist Directories and Create index.js<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#Step_13_Create_webpackconfigjs_and_Enable_CORS\" title=\"Step 1.3: Create webpack.config.js and Enable CORS\">Step 1.3: Create webpack.config.js and Enable CORS<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#Step_2_Import_FusionCharts_Libraries\" title=\"Step 2: Import FusionCharts Libraries\">Step 2: Import FusionCharts Libraries<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#Step_3_Write_the_Top_Level_Functions\" title=\"Step 3: Write the Top Level Functions\">Step 3: Write the Top Level Functions<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#Step_4_Convert_the_Data_to_JSON\" title=\"Step 4: Convert the Data to JSON\">Step 4: Convert the Data to JSON<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#Step_41_Convert_the_Data_to_Matrix\" title=\"Step 4.1: Convert the Data to Matrix\">Step 4.1: Convert the Data to Matrix<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#Step_42_Create_the_JSON_Object_for_Dataset_Key\" title=\"Step 4.2: Create the JSON Object for Dataset Key\">Step 4.2: Create the JSON Object for Dataset Key<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#Step_43_Create_JSON_for_Datasource_Key\" title=\"Step 4.3: Create JSON for Datasource Key\">Step 4.3: Create JSON for Datasource Key<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#Step_5_Render_the_Multi-Series_Chart\" title=\"Step 5: Render the Multi-Series Chart\">Step 5: Render the Multi-Series Chart<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#Step_6_Running_the_App\" title=\"Step 6: Running the App\">Step 6: Running the App<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/#Can_You_Create_More_Data_Visualizations_Using_Javascript\" title=\"Can You Create More Data Visualizations Using Javascript?\">Can You Create More Data Visualizations Using Javascript?<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"About_the_Auto-mpg_Dataset\"><\/span>About the Auto-mpg Dataset<span class=\"ez-toc-section-end\"><\/span><\/h2>\r\n<span data-preserver-spaces=\"true\">The machine learning community uses the auto-mpg dataset to test the accuracy of a regression model. It contains the information of city-cycle fuel consumption in miles per gallon of different cars and different attributes like cylinders, displacement, horsepower, weight, etc. We&#8217;ll use horsepower as the predictor variable for various brands of automobiles and create a multi-series scatter plot with fuel consumption as the dependent variable.<\/span>\r\n<h2><span class=\"ez-toc-section\" id=\"The_Multi-Series_Chart\"><\/span>The Multi-Series Chart<span class=\"ez-toc-section-end\"><\/span><\/h2>\r\nThe final multi-series scatter plot for the auto-mpg dataset looks as follows:\r\n\r\n<img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18101 size-large\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/2021\/06\/scatter-1024x536.png\" alt=\"\" width=\"640\" height=\"335\" srcset=\"\/blog\/wp-content\/uploads\/2021\/06\/scatter-1024x536.png 1024w, \/blog\/wp-content\/uploads\/2021\/06\/scatter-300x157.png 300w, \/blog\/wp-content\/uploads\/2021\/06\/scatter-768x402.png 768w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/>\r\n\r\n<span data-preserver-spaces=\"true\">The plot has the following valuable features:<\/span>\r\n<ol>\r\n \t<li><span data-preserver-spaces=\"true\">Individual data points for different brands of cars are shown in different colors.<\/span><\/li>\r\n \t<li><span data-preserver-spaces=\"true\">The corresponding regression line for each vehicle is generated automatically and shown in the car&#8217;s corresponding color.<\/span><\/li>\r\n \t<li><span data-preserver-spaces=\"true\">Clicking on the legend below turns the plot of a specific car on or off.<\/span><\/li>\r\n \t<li><span data-preserver-spaces=\"true\">Hovering the mouse on a data point shows its information in detail.<\/span><\/li>\r\n \t<li><span data-preserver-spaces=\"true\">Everything in the plot, from the axis labels to the title and sub-title, is configurable.<\/span><\/li>\r\n<\/ol>\r\n<span data-preserver-spaces=\"true\">Let&#8217;s get started on building this app.<\/span>\r\n<h2><span class=\"ez-toc-section\" id=\"Step_1_Setup_the_Webpack_Project\"><\/span>Step 1: Setup the Webpack Project<span class=\"ez-toc-section-end\"><\/span><\/h2>\r\nLet&#8217;s create a new directory for the project and name it multiseriesChart. At the console, change the directory to the empty project directory and follow the given steps:\r\n<h3><span class=\"ez-toc-section\" id=\"Step_11_Install_Webpack_and_FusionCharts\"><\/span>Step 1.1: Install Webpack and FusionCharts<span class=\"ez-toc-section-end\"><\/span><\/h3>\r\n<span style=\"font-weight: 400\">Type the following at the console:<\/span>\r\n<pre class=\"lang:bash\">npm i -D webpack-dev-server html-webpack-plugin path webpack-cli fusioncharts<\/pre>\r\n<h3><span class=\"ez-toc-section\" id=\"Step_12_Make_srcdist_Directories_and_Create_indexjs\"><\/span>Step 1.2: Make src+dist Directories and Create index.js<span class=\"ez-toc-section-end\"><\/span><\/h3>\r\n<span style=\"font-weight: 400\">Enter the three commands at the console:<\/span>\r\n<pre class=\"lang:bash\">mkdir src\r\n\r\ntouch src\/index.js\r\n\r\nmkdir dist<\/pre>\r\n<span style=\"font-weight: 400\">The entire code for the data conversion and chart rendering will go into the index.js file.<\/span>\r\n<h3><span class=\"ez-toc-section\" id=\"Step_13_Create_webpackconfigjs_and_Enable_CORS\"><\/span>Step 1.3: Create webpack.config.js and Enable CORS<span class=\"ez-toc-section-end\"><\/span><\/h3>\r\n<span style=\"font-weight: 400\">Create an empty file called webpack.config.js in the main project directory and add the following code to it:<\/span>\r\n<pre class=\"lang:javascript\">\/\/ webpack.config.js\r\nconst HtmlWebPackPlugin = require( 'html-webpack-plugin' );\r\nconst path = require( 'path' );\r\nmodule.exports = {\r\n\u00a0\u00a0 context: __dirname,\r\n\u00a0\u00a0 entry: '.\/src\/index.js',\r\n\u00a0\u00a0 output: {\r\n\u00a0 \u00a0 \u00a0 path: path.resolve( __dirname, 'dist' ),\r\n\u00a0 \u00a0 \u00a0 filename: 'main.js',\r\n\u00a0\u00a0 },\r\n\u00a0\u00a0 plugins: [\r\n\u00a0 \u00a0 \u00a0 new HtmlWebPackPlugin()\r\n\u00a0\u00a0 ],\r\n\u00a0\u00a0 devServer: {\r\n\u00a0\u00a0 \u00a0 \u00a0 headers: {\r\n\u00a0\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \"Access-Control-Allow-Origin\": \"*\",\r\n\u00a0\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \"Access-Control-Allow-Methods\": \"GET, POST, PUT, DELETE, PATCH, OPTIONS\",\r\n\u00a0\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \"Access-Control-Allow-Headers\": \"X-Requested-With, content-type, Authorization\"\r\n\u00a0\u00a0 \u00a0 \u00a0 \u00a0 },\r\n\u00a0\u00a0 \u00a0 \u00a0 proxy: {\r\n\u00a0\u00a0 \u00a0 \u00a0 \u00a0 '\/mlRepo': {\r\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 target: 'https:\/\/archive.ics.uci.edu',\r\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 pathRewrite: { '^\/mlRepo': '\/ml\/machine-learning-databases\/auto-mpg\/auto-mpg.data' },\r\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 changeOrigin: true,\r\n\u00a0\u00a0 \u00a0 \u00a0 \u00a0 },\r\n\u00a0\u00a0 \u00a0 \u00a0 },\r\n\u00a0\u00a0 \u00a0 }\r\n};<\/pre>\r\n<h2><span class=\"ez-toc-section\" id=\"Step_2_Import_FusionCharts_Libraries\"><\/span>Step 2: Import FusionCharts Libraries<span class=\"ez-toc-section-end\"><\/span><\/h2>\r\nOpen the file index.js. Import the FusionCharts themes and chart types by adding the following code to it:\r\n<pre class=\"lang:javascript\">\/\/ Include the core fusioncharts file from core\u00a0\r\n\r\nimport FusionCharts from 'fusioncharts\/core';\r\n\r\n\/\/ Include the chart from the viz folder\r\n\r\n\/\/ E.g. - import ChartType from fusioncharts\/viz\/[ChartType]\r\n\r\nimport Scatter from 'fusioncharts\/viz\/scatter';\r\n\r\n\/\/ Include the fusion theme\r\n\r\nimport FusionTheme from 'fusioncharts\/themes\/es\/fusioncharts.theme.fusion';\r\n\r\nAlso, add a div tag for the multi-series scatter plot container as follows:\r\n\r\n\/\/add the div tag for the chart container\r\n\r\nconst myDiv = document.createElement('div');\r\n\r\nmyDiv.id = 'chart-container';\r\n\r\ndocument.body.appendChild( myDiv );<\/pre>\r\n<h2><span class=\"ez-toc-section\" id=\"Step_3_Write_the_Top_Level_Functions\"><\/span>Step 3: Write the Top Level Functions<span class=\"ez-toc-section-end\"><\/span><\/h2>\r\nAdd main() and renderPage() functions to index.js file.\r\n<pre class=\"lang:markup\">async function main() {\r\n\u00a0 \u00a0 \/\/Get the data\r\n\u00a0 \u00a0 let response = await fetch('\/mlRepo');\r\n\u00a0 \u00a0 let data = await response.text();\r\n\u00a0 \u00a0 if (response.ok){ \u00a0 \u00a0 \u00a0 \u00a0\r\n\u00a0 \u00a0 \u00a0 \u00a0 renderPage(data);\r\n\u00a0 \u00a0 }\r\n\u00a0 \u00a0 else {\r\n\u00a0 \u00a0 \u00a0 \u00a0 alert('Error reading data from ML repository');\r\n\u00a0 \u00a0 }\r\n}\r\n\/\/renders the html page when passed data as text\r\nfunction renderPage(text){\r\n\u00a0 \u00a0 var classes=[\"chevrolet\",\"ford\",\"toyota\"];\r\n\u00a0 \u00a0 var matrix = textToMatrix(text);\r\n\u00a0 \u00a0 var dataset = convertMatrixToJson(matrix,classes);\r\n\u00a0 \u00a0 var dataSource = constructDataSource(dataset);\r\n\u00a0 \u00a0 renderChart(dataSource);\r\n}<\/pre>\r\n<h2><span class=\"ez-toc-section\" id=\"Step_4_Convert_the_Data_to_JSON\"><\/span>Step 4: Convert the Data to JSON<span class=\"ez-toc-section-end\"><\/span><\/h2>\r\nFusionCharts requires data to be in JSON format for plotting. To convert the data file read from the UCI machine learning repository, we need to do the following:\r\n<h3><span class=\"ez-toc-section\" id=\"Step_41_Convert_the_Data_to_Matrix\"><\/span>Step 4.1: Convert the Data to Matrix<span class=\"ez-toc-section-end\"><\/span><\/h3>\r\nAdd the following function to index.js:\r\n<pre class=\"lang:javascript\">\/\/convert text to matrix\r\nfunction textToMatrix(text){\r\n\u00a0 \u00a0 var matrix = [];\r\n\u00a0 \u00a0 var rows = text.split(\"\\n\");\r\n\u00a0 \u00a0 for(var i=0;i&lt;rows.length;i++){\r\n\u00a0 \u00a0 \u00a0 \u00a0 var cols = rows[i].split(\/\\s+\/);\r\n\u00a0 \u00a0 \u00a0 \u00a0 if (cols.length &gt; 1)\r\n\u00a0 \u00a0 \u00a0 \u00a0 matrix.push(cols);\r\n\u00a0 \u00a0 }\r\n\u00a0 \u00a0 return matrix;\r\n}<\/pre>\r\n<h3><span class=\"ez-toc-section\" id=\"Step_42_Create_the_JSON_Object_for_Dataset_Key\"><\/span>Step 4.2: Create the JSON Object for Dataset Key<span class=\"ez-toc-section-end\"><\/span><\/h3>\r\nThe matrix created in step 4.1 can be passed to the <span class=\"s1\">convertMatrixToJson()<\/span> function to return a JSON object for the dataset key:\r\n<pre class=\"lang:javascript\">\/\/define the position of X,Y variables in data file\r\nconst CLASS_IND = 8;\r\nconst X_IND = 3;\r\nconst Y_IND = 0;\r\n\/\/returns JSON text for 'dataset' key\r\nfunction convertMatrixToJson(matrix,classes){\r\n\u00a0 \u00a0 \/\/JSON for dataset\r\n\u00a0 \u00a0 var dataset = [];\r\n\u00a0 \u00a0 var colors = [\"#0000ff\",\"#00ff00\",\"#ff0000\",\"ffff00\"];\r\n\u00a0 \u00a0 for (var k=0;k&lt;classes.length;++k)\r\n\u00a0 \u00a0 {\r\n\u00a0 \u00a0 \u00a0 \u00a0 var className = classes[k]; \u00a0 \u00a0 \u00a0 \u00a0\r\n\u00a0 \u00a0 \u00a0 \u00a0 var seriesObj = {seriesname: className,\r\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 color: colors[k],\r\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 anchorbgcolor: colors[k],\r\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 anchorbordercolor: colors[k]\r\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 };\r\n\u00a0 \u00a0 \u00a0 \u00a0 var data = [];\r\n\u00a0 \u00a0 \u00a0 \u00a0 var subset = matrix.filter(r=&gt;r[CLASS_IND].match(className));\r\n\u00a0 \u00a0 \u00a0 \u00a0 for (var i=0;i&lt;subset.length;++i)\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0\r\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 data.push({x:subset[i][X_IND],y:subset[i][Y_IND]});\r\n\u00a0 \u00a0 \u00a0 \u00a0 seriesObj.data = data;\r\n\u00a0 \u00a0 \u00a0 \u00a0 dataset.push(seriesObj);\r\n\u00a0 \u00a0 }\r\n\u00a0 \u00a0 return dataset;\r\n}<\/pre>\r\n<h3><span class=\"ez-toc-section\" id=\"Step_43_Create_JSON_for_Datasource_Key\"><\/span>Step 4.3: Create JSON for Datasource Key<span class=\"ez-toc-section-end\"><\/span><\/h3>\r\nThe following function constructs the &#8216;datasource&#8217; key for JSON. Note that the &#8220;showRegressionLine&#8221; option is set to 1, to automatically create regression lines for each car.\r\n<pre class=\"lang:javascript\">\/\/constructs JSON text for 'dataSource' key\r\nfunction constructDataSource(dataset){\r\n\u00a0 \u00a0 var dataSource = {\"chart\": {\r\n\u00a0 \u00a0 \u00a0 \u00a0 \"caption\": \"Miles Per Gallon vs. Horsepower\",\r\n\u00a0 \u00a0 \u00a0 \u00a0 \"subcaption\": \"Data Source: UCI Machine Learning Repository\",\r\n\u00a0 \u00a0 \u00a0 \u00a0 \"xAxisName\": \"Horsepower\",\r\n\u00a0 \u00a0 \u00a0 \u00a0 \"YAxisName\": \"Miles Per Gallon\",\r\n\u00a0 \u00a0 \u00a0 \u00a0 \"ynumbersuffix\": \" mpg\",\r\n\u00a0 \u00a0 \u00a0 \u00a0 \"theme\": \"fusion\",\r\n\u00a0 \u00a0 \u00a0 \u00a0 \"showRegressionLine\": \"1\",\r\n\u00a0 \u00a0 \u00a0 \u00a0 \"plotToolText\": \"&lt;b&gt;$yDataValue&lt;\/b&gt; done by a &lt;b&gt;$seriesName&lt;\/b&gt; with horsepower &lt;b&gt;$xDataValue&lt;\/b&gt;\"\r\n\u00a0 \u00a0 },\r\n\u00a0 \u00a0 dataset}; \u00a0 \u00a0\r\n\u00a0 \u00a0 return dataSource;\r\n}<\/pre>\r\n<h2><span class=\"ez-toc-section\" id=\"Step_5_Render_the_Multi-Series_Chart\"><\/span>Step 5: Render the Multi-Series Chart<span class=\"ez-toc-section-end\"><\/span><\/h2>\r\nAdd the following function to render the final multi-series scatter chart:\r\n<pre class=\"lang:javascript\">\/\/ Draw the chart\r\nfunction renderChart(dataSrc){\r\n\u00a0 \u00a0 FusionCharts.addDep(Scatter);\r\n\u00a0 \u00a0 FusionCharts.addDep(FusionTheme);\r\n\u00a0 \u00a0 \/\/Chart Configurations\r\n\u00a0 \u00a0 const chartConfig = {\r\n\u00a0 \u00a0 \u00a0 \u00a0 type: 'scatter',\r\n\u00a0 \u00a0 \u00a0 \u00a0 renderAt: 'chart-container',\r\n\u00a0 \u00a0 \u00a0 \u00a0 width: '80%',\r\n\u00a0 \u00a0 \u00a0 \u00a0 height: '600',\r\n\u00a0 \u00a0 \u00a0 \u00a0 dataFormat: 'json',\r\n\u00a0 \u00a0 \u00a0 \u00a0 dataSource: dataSrc\r\n\u00a0 \u00a0 }\r\n\u00a0 \u00a0 \/\/Create an Instance with chart options and render the chart\r\n\u00a0 \u00a0 var chartInstance = new FusionCharts(chartConfig);\r\n\u00a0 \u00a0 chartInstance.render();\r\n}<\/pre>\r\n<h2><span class=\"ez-toc-section\" id=\"Step_6_Running_the_App\"><\/span>Step 6: Running the App<span class=\"ez-toc-section-end\"><\/span><\/h2>\r\nAs a final step, you need to call the main() function to render the chart.\r\n\r\n<span style=\"font-weight: 400\">Run the webpack server by typing the following at the command line:<\/span>\r\n<pre class=\"lang:bash\">npx webpack serve --mode=development<\/pre>\r\n<span style=\"font-weight: 400\">Load the app in your browser using localhost:8080.<\/span>\r\n<h2><span class=\"ez-toc-section\" id=\"Can_You_Create_More_Data_Visualizations_Using_Javascript\"><\/span>Can You Create More Data Visualizations Using Javascript?<span class=\"ez-toc-section-end\"><\/span><\/h2>\r\n<a class=\"editor-rtfLink\" href=\"https:\/\/www.fusioncharts.com\" target=\"_blank\" rel=\"noopener noreferrer\"><span data-preserver-spaces=\"true\">FusionCharts<\/span><\/a><span data-preserver-spaces=\"true\">\u00a0is a comprehensive library of fantastic plots, maps, and graphs. You can find all kinds of interactive and beautiful visualizations for your next machine learning and data science app. FusionCharts enables you to create the next-level apps for your web and mobile platforms.<\/span>\r\n\r\n<a class=\"editor-rtfLink\" href=\"https:\/\/github.com\/fusionchartsexpress\/JavascriptMultiseriesChart\" target=\"_blank\" rel=\"noopener noreferrer\"><span data-preserver-spaces=\"true\">Download the complete source code for this app over on GitHub.<\/span><\/a>\r\n\r\n<span data-preserver-spaces=\"true\">Enjoy FusionCharts!<\/span>","protected":false},"excerpt":{"rendered":"<p>A challenging problem in machine learning and data science is that of regression analysis. Regression analysis is about finding a suitable model to estimate the relationship between two or more variables. The final model predicts a variable, also called the outcome variable, from the value of one or more predictor variables. Therefore, FusionCharts\u00a0provides an easy [&hellip;]<\/p>\n","protected":false},"author":59,"featured_media":18102,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[722],"tags":[785,105,786,783,782,784],"coauthors":[769],"class_list":["post-18099","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-fusioncharts","tag-auto-mpg-dataset","tag-data-visualization","tag-machine-learning-dataset","tag-multi-series-charts","tag-regression","tag-scatter-plots"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Interactive Multi-Series Charts for Regression Analysis 2026<\/title>\n<meta name=\"description\" content=\"Master exploratory data analysis. Learn how to add multi-series charts of regression data to your 2026 JavaScript applications with ease. Follow guide.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.fusioncharts.com\/blog\/powerful-multi-series-charts-can-visualize-machine-learning-regression-data\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Interactive Multi-Series Charts for Regression Analysis 2026\" \/>\n<meta property=\"og:description\" content=\"Master exploratory data analysis. Learn how to add multi-series charts of regression data to your 2026 JavaScript applications with ease. 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