{"id":43475,"date":"2024-04-15T21:30:00","date_gmt":"2024-04-15T21:30:00","guid":{"rendered":"https:\/\/exam.pscnotes.com\/mcq\/?p=43475"},"modified":"2024-04-15T21:30:00","modified_gmt":"2024-04-15T21:30:00","slug":"machine-learning-techniques-differ-from-statistical-techniques-in-that-machine-learning-methods","status":"publish","type":"post","link":"https:\/\/exam.pscnotes.com\/mcq\/machine-learning-techniques-differ-from-statistical-techniques-in-that-machine-learning-methods\/","title":{"rendered":"Machine learning techniques differ from statistical techniques in that machine learning methods"},"content":{"rendered":"<p>\r\n    <!-- Check if it's an AMP page -->\r\n            <!-- Non-AMP version -->\r\n        <div class=\"mcq-container\" data-quiz-id=\"quizState_6a97820ea111e\">\r\n                                            <div class=\"option\" data-option-key=\"option1\" data-is-correct=\"false\">\r\n                    typically assume an underlying distribution for the data.                <\/div>\r\n                                            <div class=\"option\" data-option-key=\"option2\" data-is-correct=\"true\">\r\n                    are better able to deal with missing and noisy data.                <\/div>\r\n                                            <div class=\"option\" data-option-key=\"option3\" data-is-correct=\"false\">\r\n                    are not able to explain their behavior.                <\/div>\r\n                                            <div class=\"option\" data-option-key=\"option4\" data-is-correct=\"false\">\r\n                    have trouble with large-sized datasets.                <\/div>\r\n                            \r\n            <!-- Feedback messages for non-AMP -->\r\n            <div class=\"feedback\" data-feedback=\"wrong\">Answer is Right!<\/div>\r\n            <div class=\"feedback\" data-feedback=\"right\">Answer is Wrong!<\/div>\r\n        <\/div>\r\n\r\n        <script>\r\n        document.addEventListener('DOMContentLoaded', function () {\r\n            var containers = document.querySelectorAll('.mcq-container');\r\n\r\n            containers.forEach(function(container) {\r\n                var options = container.querySelectorAll('.option');\r\n                var feedbackSelect = container.querySelector('[data-feedback=\"select\"]');\r\n                var feedbackWrong = container.querySelector('[data-feedback=\"wrong\"]');\r\n                var feedbackRight = container.querySelector('[data-feedback=\"right\"]');\r\n\r\n                options.forEach(function(option) {\r\n                    option.addEventListener('click', function() {\r\n                        var selectedOption = option.getAttribute('data-option-key');\r\n                        var isCorrect = option.getAttribute('data-is-correct') === 'true';\r\n\r\n                        \/\/ Remove previous selections\r\n                        options.forEach(function(opt) {\r\n                            opt.classList.remove('correct', 'incorrect');\r\n                        });\r\n\r\n                        \/\/ Add the correct\/incorrect class\r\n                        if (isCorrect) {\r\n                            option.classList.add('correct');\r\n                            feedbackRight.hidden = false;\r\n                            feedbackWrong.hidden = true;\r\n                        } else {\r\n                            option.classList.add('incorrect');\r\n                            feedbackRight.hidden = true;\r\n                            feedbackWrong.hidden = false;\r\n                        }\r\n\r\n                        \/\/ Hide select feedback\r\n                        feedbackSelect.hidden = true;\r\n                    });\r\n                });\r\n            });\r\n        });\r\n        <\/script>\r\n    \r\n    <!--more--><\/p>\n<p>The correct answer is: <strong>B. are better able to deal with missing and noisy data.<\/strong><\/p>\n<p>Machine learning techniques are better able to deal with missing and noisy data than statistical techniques because they are not based on any assumptions about the data. This means that they can learn from data that is incomplete or inaccurate, which can be very useful in real-world applications.<\/p>\n<p>Statistical techniques, on the other hand, are based on assumptions about the data. These assumptions can be about the distribution of the data, the relationships between variables, <div class=\"youtube-subscribe-container\">\r\n        <a href=\"https:\/\/www.youtube.com\/channel\/UCNHT8lW-JmLC68rjBfZhdkg?sub_confirmation=1\" target=\"_blank\" class=\"youtube-subscribe-button\">\r\n            <span class=\"youtube-icon\">\r\n                <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 576 512\">\r\n                    <path d=\"M549.7 124.1c-6.3-23.7-24.8-42.3-48.3-48.6C458.8 64 288 64 288 64S117.2 64 74.6 75.5c-23.5 6.3-42 24.9-48.3 48.6-11.4 42.9-11.4 132.3-11.4 132.3s0 89.4 11.4 132.3c6.3 23.7 24.8 41.5 48.3 47.8C117.2 448 288 448 288 448s170.8 0 213.4-11.5c23.5-6.3 42-24.2 48.3-47.8 11.4-42.9 11.4-132.3 11.4-132.3s0-89.4-11.4-132.3zm-317.5 213.5V175.2l142.7 81.2-142.7 81.2z\"\/>\r\n                <\/svg>\r\n            <\/span>\r\n            Subscribe on YouTube\r\n        <\/a>\r\n    <\/div> or the presence of outliers. If these assumptions are not met, then the results of the statistical analysis can be unreliable.<\/p>\n<p>For example, let&#8217;s say you want to predict the price of a house. You could use a statistical technique to fit a model to the data of houses that have already sold. However, this model would only be accurate if the data is representative of all houses on the market. If there are a lot of missing values in the data, or if the data is noisy, then the model will not be very accurate.<\/p>\n<p>On the other hand, you could use a machine learning technique to predict the price of a house. Machine learning techniques can learn from data that is incomplete or inaccurate, so they would be able to produce a more accurate prediction than a statistical technique.<\/p>\n<p>In addition, machine learning techniques are often more robust to outliers than statistical techniques. Outliers are data points that are very different from the rest of the data. They can cause problems for statistical techniques, because they can make the model fit the data too closely and not generalize well to new data. Machine learning techniques are less likely to be affected by outliers, because they are not based on any assumptions about the data.<\/p>\n<p>Overall, machine <div class=\"telegram-channel-container\">\r\n        <a href=\"https:\/\/t.me\/pscnotes2025\" target=\"_blank\" class=\"telegram-channel-button\">\r\n            <span class=\"telegram-icon\">\r\n                <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 496 512\">\r\n                    <path fill=\"white\" d=\"M248,8C111,8,0,119,0,256s111,248,248,248s248-111,248-248S385,8,248,8z M362,177L320,367c-3,14-10,18-20,14l-56-41l-27,26 c-3,3-5,5-10,5l4-63L323,196c5-5-1-7-8-3l-98,62l-42-13c-9-3-10-9,2-14l162-63C351,160,365,164,362,177z\"\/>\r\n                <\/svg>\r\n            <\/span>\r\n            Join Our Telegram Channel\r\n        <\/a>\r\n    <\/div> learning techniques are better able to deal with missing and noisy data than statistical techniques. This is because they are not based on any assumptions about the data, and they are often more robust to outliers.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Join Our Telegram Channel Subscribe on YouTube<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[729],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.2 (Yoast SEO v23.3) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Machine learning techniques differ from statistical techniques in that machine learning methods<\/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:\/\/exam.pscnotes.com\/mcq\/machine-learning-techniques-differ-from-statistical-techniques-in-that-machine-learning-methods\/\" \/>\n<meta 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