{"id":69533,"date":"2025-08-13T00:49:30","date_gmt":"2025-08-13T00:49:30","guid":{"rendered":"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/"},"modified":"2025-08-13T00:49:30","modified_gmt":"2025-08-13T00:49:30","slug":"20-feature-engineering-quiz-questions-and-answers","status":"publish","type":"post","link":"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/","title":{"rendered":"20 Feature Engineering Quiz Questions and Answers"},"content":{"rendered":"<p>Feature engineering is a crucial process in data science and machine learning that involves transforming raw data into meaningful features to improve model performance. This includes selecting, modifying, or creating new variables from the original dataset to better capture patterns, relationships, and insights. For instance, techniques like scaling numerical data, encoding categorical variables, handling missing values, and deriving new features through operations such as aggregation or polynomial transformations help models learn more effectively. By leveraging domain knowledge, feature engineering reduces noise, enhances predictive accuracy, and prevents overfitting, ultimately leading to more robust and interpretable results.<\/p>\n<h3>Table of contents<\/h3>\n<ul class=\"article_list\">\n<li><a href=\"#1\">Part 1: Create an amazing feature engineering quiz using AI instantly in OnlineExamMaker<\/a><\/li>\n<li><a href=\"#2\">Part 2: 20 feature engineering quiz questions &#038; answers<\/a><\/li>\n<li><a href=\"#3\">Part 3: Save time and energy: generate quiz questions with AI technology <\/a><\/li>\n<\/ul>\n<p><img decoding=\"async\" src=\"https:\/\/onlineexammaker.com\/kb\/wp-content\/uploads\/2025\/08\/1742-feature-engineering.webp\" alt=\"\"\/><\/p>\n<h3 id=\"1\">Part 1: Create an amazing feature engineering quiz using AI instantly in OnlineExamMaker<\/h3>\n<p>Nowadays more and more people create feature engineering quizzes using AI technologies, OnlineExamMaker a powerful AI-based quiz making tool that can save you time and efforts. The software makes it simple to design and launch interactive quizzes, assessments, and surveys. With the Question Editor, you can create multiple-choice, open-ended, matching, sequencing and many other types of questions for your tests, exams and inventories. You are allowed to enhance quizzes with multimedia elements like images, audio, and video to make them more interactive and visually appealing.<\/p>\n<p><strong>Recommended features for you:<\/strong><br \/>\n\u25cf Prevent cheating by randomizing questions or changing the order of questions, so learners don&#8217;t get the same set of questions each time.<br \/>\n\u25cf Automatically generates detailed reports\u2014individual scores, question report, and group performance.<br \/>\n\u25cf Simply copy a few lines of codes, and add them to a web page, you can present your online quiz in your website, blog, or landing page.<br \/>\n\u25cf Offers question analysis to evaluate question performance and reliability, helping instructors optimize their training plan.<\/p>\n<div class=\"embed_video_blog\">\n<div class=\"embed-responsive embed-responsive-16by9\" style=\"margin-bottom:16px;\">\n <iframe class=\"embed-responsive-item\" src=\"https:\/\/www.youtube.com\/embed\/zlqho9igH2Y\"><\/iframe>\n<\/div>\n<\/div>\n<div class=\"getstarted-container\">\n<p style=\"margin-bottom: 13px;\">Automatically generate questions using AI<\/p>\n<div class=\"blog_double_btn clearfix\">\n<div class=\"col-sm-6  col-xs-12\">\n<div class=\"p-style-a\"><a class=\"get_started_btn\" href=\"https:\/\/onlineexammaker.com\/features\/ai-question-generator.html?refer=download_questions\" target=\"_blank\" rel=\"noopener\">Try AI Question Generator<\/a><\/div>\n<div class=\"p-style-b\">Generate questions for any topic<\/div>\n<\/div>\n<div class=\"col-sm-6  col-xs-12\">\n<div class=\"p-style-a\"><a class=\"get_started_btn\" href=\"https:\/\/onlineexammaker.com\/sign-up.html?refer=blog_btn\"> Create A Quiz<\/a><\/div>\n<div class=\"p-style-b\">100% free forever<\/div>\n<\/div>\n<\/div>\n<\/div>\n<h3 id=\"2\">Part 2: 20 feature engineering quiz questions &#038; answers<\/h3>\n<p><button id=\"copyquestionsBtn\" type=\"button\" onclick=\"myFunction()\">Copy Quiz Questions<\/button>\u00a0\u00a0or\u00a0\u00a0<button id=\"genquestionsBtn\" class=\"genbtnstyle\" type=\"button\" onclick=\"myFunction1()\">Generate Questions using AI<\/button><\/p>\n<div id=\"copy_questions\">\n<p>1. <strong>Question<\/strong>: What is the primary purpose of feature engineering in machine learning?<br \/>\n   A. To increase the size of the dataset<br \/>\n   B. To create new features that improve model performance<br \/>\n   C. To visualize data patterns<br \/>\n   D. To reduce computational resources<br \/>\n   <strong>Answer<\/strong>: B<br \/>\n   <strong>Explanation<\/strong>: Feature engineering transforms raw data into a format that is more suitable for machine learning algorithms, helping models learn patterns more effectively and achieve better accuracy.<\/p>\n<p>2. <strong>Question<\/strong>: Which technique is commonly used to convert categorical variables into numerical ones?<br \/>\n   A. Normalization<br \/>\n   B. One-hot encoding<br \/>\n   C. Standardization<br \/>\n   D. Binning<br \/>\n   <strong>Answer<\/strong>: B<br \/>\n   <strong>Explanation<\/strong>: One-hot encoding creates binary columns for each category, allowing machine learning models to handle categorical data without assuming ordinal relationships.<\/p>\n<p>3. <strong>Question<\/strong>: What does feature scaling aim to achieve?<br \/>\n   A. Remove outliers from the dataset<br \/>\n   B. Ensure all features contribute equally to the model<br \/>\n   C. Increase the number of features<br \/>\n   D. Convert text data into numbers<br \/>\n   <strong>Answer<\/strong>: B<br \/>\n   <strong>Explanation<\/strong>: Feature scaling adjusts the range of features so that they have a similar scale, preventing features with larger ranges from dominating the model during training.<\/p>\n<p>4. <strong>Question<\/strong>: Which method is used for handling missing values in a dataset?<br \/>\n   A. Imputation<br \/>\n   B. Deletion<br \/>\n   C. Both A and B<br \/>\n   D. Neither A nor B<br \/>\n   <strong>Answer<\/strong>: C<br \/>\n   <strong>Explanation<\/strong>: Imputation replaces missing values with estimated ones (e.g., mean), while deletion removes rows or columns with missing data, depending on the context to maintain data integrity.<\/p>\n<p>5. <strong>Question<\/strong>: What is the difference between label encoding and one-hot encoding?<br \/>\n   A. Label encoding is for numerical data only<br \/>\n   B. One-hot encoding creates more columns than label encoding<br \/>\n   C. Label encoding is used for images<br \/>\n   D. Both are identical<br \/>\n   <strong>Answer<\/strong>: B<br \/>\n   <strong>Explanation<\/strong>: Label encoding assigns a unique integer to each category, which can imply ordinality, whereas one-hot encoding expands the dataset with binary columns, avoiding any ordinal assumptions.<\/p>\n<p>6. <strong>Question<\/strong>: In feature selection, what does the chi-squared test evaluate?<br \/>\n   A. Correlation between features<br \/>\n   B. Independence between features and the target variable<br \/>\n   C. The mean of features<br \/>\n   D. The variance of features<br \/>\n   <strong>Answer<\/strong>: B<br \/>\n   <strong>Explanation<\/strong>: The chi-squared test assesses the dependence between categorical features and the target, helping to select features that are most relevant for prediction.<\/p>\n<p>7. <strong>Question<\/strong>: Which of the following is an example of a derived feature?<br \/>\n   A. Raw data from a sensor<br \/>\n   B. The ratio of two existing features<br \/>\n   C. A randomly generated number<br \/>\n   D. The original target variable<br \/>\n   <strong>Answer<\/strong>: B<br \/>\n   <strong>Explanation<\/strong>: Derived features, like ratios or differences, are created from existing data to capture new relationships that can enhance model performance.<\/p>\n<p>8. <strong>Question<\/strong>: What is binning in feature engineering?<br \/>\n   A. Grouping continuous data into categories<br \/>\n   B. Removing duplicate entries<br \/>\n   C. Scaling data to a range<br \/>\n   D. Encoding text data<br \/>\n   <strong>Answer<\/strong>: A<br \/>\n   <strong>Explanation<\/strong>: Binning converts continuous variables into discrete bins, which can simplify the data and help models handle non-linear relationships.<\/p>\n<p>9. <strong>Question<\/strong>: Which normalization technique scales data to a range between 0 and 1?<br \/>\n   A. Standardization<br \/>\n   B. Min-Max scaling<br \/>\n   C. Z-score normalization<br \/>\n   D. Log transformation<br \/>\n   <strong>Answer<\/strong>: B<br \/>\n   <strong>Explanation<\/strong>: Min-Max scaling rescales features to a fixed range, typically 0 to 1, based on the minimum and maximum values, making it useful for algorithms sensitive to data magnitude.<\/p>\n<p>10. <strong>Question<\/strong>: How does polynomial features help in feature engineering?<br \/>\n    A. By reducing the dataset size<br \/>\n    B. By creating interactions between features<br \/>\n    C. By deleting irrelevant features<br \/>\n    D. By converting categorical data<br \/>\n    <strong>Answer<\/strong>: B<br \/>\n    <strong>Explanation<\/strong>: Polynomial features generate new features by raising existing ones to powers and multiplying them, capturing non-linear relationships in the data.<\/p>\n<p>11. <strong>Question<\/strong>: What is the role of TF-IDF in text feature engineering?<br \/>\n    A. To count word frequencies<br \/>\n    B. To weigh word importance in a document relative to a corpus<br \/>\n    C. To remove stop words<br \/>\n    D. To translate text into numbers<br \/>\n    <strong>Answer<\/strong>: B<br \/>\n    <strong>Explanation<\/strong>: TF-IDF assigns weights to words based on their frequency in a document and rarity in the entire corpus, highlighting significant terms for text analysis.<\/p>\n<p>12. <strong>Question<\/strong>: Which feature engineering technique is useful for time series data?<br \/>\n    A. Lag features<br \/>\n    B. One-hot encoding<br \/>\n    C. Normalization<br \/>\n    D. All of the above<br \/>\n    <strong>Answer<\/strong>: A<br \/>\n    <strong>Explanation<\/strong>: Lag features incorporate past values of a time series as inputs, helping models capture temporal dependencies and patterns.<\/p>\n<p>13. <strong>Question<\/strong>: In feature engineering, what does correlation analysis help with?<br \/>\n    A. Identifying multicollinearity between features<br \/>\n    B. Predicting the target variable<br \/>\n    C. Visualizing data distributions<br \/>\n    D. Encoding categorical variables<br \/>\n    <strong>Answer<\/strong>: A<br \/>\n    <strong>Explanation<\/strong>: Correlation analysis detects highly correlated features, which can lead to multicollinearity, allowing engineers to remove redundant features for better model stability.<\/p>\n<p>14. <strong>Question<\/strong>: What is the purpose of feature extraction in high-dimensional data?<br \/>\n    A. To increase dimensionality<br \/>\n    B. To reduce the number of features while retaining information<br \/>\n    C. To add noise to the data<br \/>\n    D. To encode labels<br \/>\n    <strong>Answer<\/strong>: B<br \/>\n    <strong>Explanation<\/strong>: Feature extraction techniques, like PCA, transform data into a lower-dimensional space, reducing complexity without losing critical information.<\/p>\n<p>15. <strong>Question<\/strong>: Which method is best for handling imbalanced datasets in feature engineering?<br \/>\n    A. Oversampling the minority class<br \/>\n    B. Creating synthetic features<br \/>\n    C. Both A and techniques like SMOTE<br \/>\n    D. Ignoring the imbalance<br \/>\n    <strong>Answer<\/strong>: C<br \/>\n    <strong>Explanation<\/strong>: Oversampling or synthetic methods like SMOTE generate additional samples for the minority class, ensuring features are balanced to improve model generalization.<\/p>\n<p>16. <strong>Question<\/strong>: What is domain knowledge&#8217;s role in feature engineering?<br \/>\n    A. It has no role<br \/>\n    B. It guides the creation of meaningful features<br \/>\n    C. It is only used for data cleaning<br \/>\n    D. It replaces machine learning algorithms<br \/>\n    <strong>Answer<\/strong>: B<br \/>\n    <strong>Explanation<\/strong>: Domain knowledge helps identify relevant features and transformations based on real-world context, leading to more effective and interpretable models.<\/p>\n<p>17. <strong>Question<\/strong>: How does log transformation aid feature engineering?<br \/>\n    A. By making data more linear<br \/>\n    B. By increasing skewness<br \/>\n    C. By removing categorical variables<br \/>\n    D. By standardizing data<br \/>\n    <strong>Answer<\/strong>: A<br \/>\n    <strong>Explanation<\/strong>: Log transformation stabilizes variance and makes skewed data more normally distributed, which is beneficial for linear models and improving feature relationships.<\/p>\n<p>18. <strong>Question<\/strong>: What is recursive feature elimination (RFE)?<br \/>\n    A. A method to add features recursively<br \/>\n    B. A technique to remove features based on model performance<br \/>\n    C. A way to encode data<br \/>\n    D. A visualization tool<br \/>\n    <strong>Answer<\/strong>: B<br \/>\n    <strong>Explanation<\/strong>: RFE uses a model to iteratively remove the least important features, selecting an optimal subset that maximizes predictive power.<\/p>\n<p>19. <strong>Question<\/strong>: Which of the following is a disadvantage of one-hot encoding?<br \/>\n    A. It increases dataset size significantly<br \/>\n    B. It only works for numerical data<br \/>\n    C. It removes all categories<br \/>\n    D. It is not used in machine learning<br \/>\n    <strong>Answer<\/strong>: A<br \/>\n    <strong>Explanation<\/strong>: One-hot encoding can lead to a high-dimensional dataset, potentially causing the curse of dimensionality and increased computational costs.<\/p>\n<p>20. <strong>Question<\/strong>: In feature engineering, why is feature importance analysis useful?<br \/>\n    A. To complicate the model<br \/>\n    B. To identify and prioritize key features for better predictions<br \/>\n    C. To add random features<br \/>\n    D. To ignore the target variable<br \/>\n    <strong>Answer<\/strong>: B<br \/>\n    <strong>Explanation<\/strong>: Feature importance analysis, often from models like Random Forests, helps engineers focus on the most influential features, streamlining the dataset and improving efficiency.<\/p>\n<\/div>\n<p><button id=\"copyquestionsBtn\" type=\"button\" onclick=\"myFunction()\">Copy Quiz Questions<\/button>\u00a0\u00a0or\u00a0\u00a0<button id=\"genquestionsBtn\" class=\"genbtnstyle\" type=\"button\" onclick=\"myFunction1()\">Generate Questions using AI<\/button><\/p>\n<h3 id=\"3\">Part 3: Save time and energy: generate quiz questions with AI technology<\/h3>\n<div class=\"embed_video_blog\">\n<div class=\"embed-responsive embed-responsive-16by9\" style=\"margin-bottom:16px;\">\n <iframe class=\"embed-responsive-item\" src=\"https:\/\/www.youtube.com\/embed\/zlqho9igH2Y\"><\/iframe>\n<\/div>\n<\/div>\n<div class=\"getstarted-container\">\n<p style=\"margin-bottom: 13px;\">Automatically generate questions using AI<\/p>\n<div class=\"blog_double_btn clearfix\">\n<div class=\"col-sm-6  col-xs-12\">\n<div class=\"p-style-a\"><a class=\"get_started_btn\" href=\"https:\/\/onlineexammaker.com\/features\/ai-question-generator.html?refer=download_questions\" target=\"_blank\" rel=\"noopener\">Try AI Question Generator<\/a><\/div>\n<div class=\"p-style-b\">Generate questions for any topic<\/div>\n<\/div>\n<div class=\"col-sm-6  col-xs-12\">\n<div class=\"p-style-a\"><a class=\"get_started_btn\" href=\"https:\/\/onlineexammaker.com\/sign-up.html?refer=blog_btn\"> Create A Quiz<\/a><\/div>\n<div class=\"p-style-b\">100% free forever<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><script src=\"https:\/\/unpkg.com\/@popperjs\/core@2\"><\/script><br \/>\n<script src=\"https:\/\/unpkg.com\/tippy.js@6\"><\/script><\/p>\n<p><script type=\"text\/javascript\">\nfunction myFunction() {\nvar copyText = document.getElementById(\"copy_questions\");console.log(copyText.innerText);navigator.clipboard.writeText(copyText.innerText);\n}\nfunction myFunction1() {\n\u00a0  \u00a0 \u00a0 window.open(\"https:\/\/onlineexammaker.com\/features\/ai-question-generator.html\");\n\u00a0 }\nvar copy1, copy2;\n        tippy('#copyquestionsBtn', {\n        'content': \"Copy questions to clipboard\",\n       trigger: 'mouseenter',\n       'onCreate':function(instance){\n              copy1 = instance;\n       },\n       'onTrigger' : function(instance, event) {\n              copy2.hide();\n       }\n       });\n       tippy('#copyquestionsBtn', {\n       'content': \"Copied successfully\",\n       trigger: 'click',\n       'onCreate':function(instance){\n              copy2 = instance;\n       },\n       'onTrigger' : function(instance, event) {\n              copy1.hide();\n       }\n       });\ntippy('#genquestionsBtn', {\n        'content': \"Generate questions using AI for free\",\n         trigger: 'mouseenter'\n       });\n<\/script><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Feature engineering is a crucial process in data science and machine learning that involves transforming raw data into meaningful features to improve model performance. This includes selecting, modifying, or creating new variables from the original dataset to better capture patterns, relationships, and insights. For instance, techniques like scaling numerical data, encoding categorical variables, handling missing [&hellip;]<\/p>\n","protected":false},"author":8,"featured_media":69260,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[353],"tags":[],"class_list":["post-69533","post","type-post","status-publish","format-standard","hentry","category-questions-answers"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>20 Feature Engineering Quiz Questions and Answers - OnlineExamMaker Blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"20 Feature Engineering Quiz Questions and Answers - OnlineExamMaker Blog\" \/>\n<meta property=\"og:description\" content=\"Feature engineering is a crucial process in data science and machine learning that involves transforming raw data into meaningful features to improve model performance. This includes selecting, modifying, or creating new variables from the original dataset to better capture patterns, relationships, and insights. For instance, techniques like scaling numerical data, encoding categorical variables, handling missing [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/\" \/>\n<meta property=\"og:site_name\" content=\"OnlineExamMaker Blog\" \/>\n<meta property=\"article:published_time\" content=\"2025-08-13T00:49:30+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/onlineexammaker.com\/kb\/wp-content\/uploads\/2025\/08\/1742-feature-engineering.webp\" \/>\n<meta name=\"author\" content=\"Rebecca\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Rebecca\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"8 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/\",\"url\":\"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/\",\"name\":\"20 Feature Engineering Quiz Questions and Answers - OnlineExamMaker Blog\",\"isPartOf\":{\"@id\":\"https:\/\/onlineexammaker.com\/kb\/#website\"},\"datePublished\":\"2025-08-13T00:49:30+00:00\",\"dateModified\":\"2025-08-13T00:49:30+00:00\",\"author\":{\"@id\":\"https:\/\/onlineexammaker.com\/kb\/#\/schema\/person\/8447ed5937ab8046fa68476e432b32b2\"},\"breadcrumb\":{\"@id\":\"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/onlineexammaker.com\/kb\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"20 Feature Engineering Quiz Questions and Answers\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/onlineexammaker.com\/kb\/#website\",\"url\":\"https:\/\/onlineexammaker.com\/kb\/\",\"name\":\"OnlineExamMaker Blog\",\"description\":\"OnlineExamMaker\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/onlineexammaker.com\/kb\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/onlineexammaker.com\/kb\/#\/schema\/person\/8447ed5937ab8046fa68476e432b32b2\",\"name\":\"Rebecca\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/onlineexammaker.com\/kb\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/5f03edf06dd3745ea73e610a6d830a63?s=96&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/5f03edf06dd3745ea73e610a6d830a63?s=96&r=g\",\"caption\":\"Rebecca\"},\"url\":\"https:\/\/onlineexammaker.com\/kb\/author\/rebeccaoem\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"20 Feature Engineering Quiz Questions and Answers - OnlineExamMaker Blog","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/","og_locale":"en_US","og_type":"article","og_title":"20 Feature Engineering Quiz Questions and Answers - OnlineExamMaker Blog","og_description":"Feature engineering is a crucial process in data science and machine learning that involves transforming raw data into meaningful features to improve model performance. This includes selecting, modifying, or creating new variables from the original dataset to better capture patterns, relationships, and insights. For instance, techniques like scaling numerical data, encoding categorical variables, handling missing [&hellip;]","og_url":"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/","og_site_name":"OnlineExamMaker Blog","article_published_time":"2025-08-13T00:49:30+00:00","og_image":[{"url":"https:\/\/onlineexammaker.com\/kb\/wp-content\/uploads\/2025\/08\/1742-feature-engineering.webp"}],"author":"Rebecca","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Rebecca","Est. reading time":"8 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/","url":"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/","name":"20 Feature Engineering Quiz Questions and Answers - OnlineExamMaker Blog","isPartOf":{"@id":"https:\/\/onlineexammaker.com\/kb\/#website"},"datePublished":"2025-08-13T00:49:30+00:00","dateModified":"2025-08-13T00:49:30+00:00","author":{"@id":"https:\/\/onlineexammaker.com\/kb\/#\/schema\/person\/8447ed5937ab8046fa68476e432b32b2"},"breadcrumb":{"@id":"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/onlineexammaker.com\/kb\/20-feature-engineering-quiz-questions-and-answers\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/onlineexammaker.com\/kb\/"},{"@type":"ListItem","position":2,"name":"20 Feature Engineering Quiz Questions and Answers"}]},{"@type":"WebSite","@id":"https:\/\/onlineexammaker.com\/kb\/#website","url":"https:\/\/onlineexammaker.com\/kb\/","name":"OnlineExamMaker Blog","description":"OnlineExamMaker","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/onlineexammaker.com\/kb\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-US"},{"@type":"Person","@id":"https:\/\/onlineexammaker.com\/kb\/#\/schema\/person\/8447ed5937ab8046fa68476e432b32b2","name":"Rebecca","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/onlineexammaker.com\/kb\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/5f03edf06dd3745ea73e610a6d830a63?s=96&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/5f03edf06dd3745ea73e610a6d830a63?s=96&r=g","caption":"Rebecca"},"url":"https:\/\/onlineexammaker.com\/kb\/author\/rebeccaoem\/"}]}},"_links":{"self":[{"href":"https:\/\/onlineexammaker.com\/kb\/wp-json\/wp\/v2\/posts\/69533"}],"collection":[{"href":"https:\/\/onlineexammaker.com\/kb\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/onlineexammaker.com\/kb\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/onlineexammaker.com\/kb\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/onlineexammaker.com\/kb\/wp-json\/wp\/v2\/comments?post=69533"}],"version-history":[{"count":0,"href":"https:\/\/onlineexammaker.com\/kb\/wp-json\/wp\/v2\/posts\/69533\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/onlineexammaker.com\/kb\/wp-json\/wp\/v2\/media\/69260"}],"wp:attachment":[{"href":"https:\/\/onlineexammaker.com\/kb\/wp-json\/wp\/v2\/media?parent=69533"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/onlineexammaker.com\/kb\/wp-json\/wp\/v2\/categories?post=69533"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/onlineexammaker.com\/kb\/wp-json\/wp\/v2\/tags?post=69533"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}