{"id":45455,"date":"2024-04-15T21:58:16","date_gmt":"2024-04-15T21:58:16","guid":{"rendered":"https:\/\/exam.pscnotes.com\/mcq\/?p=45455"},"modified":"2024-04-15T21:58:16","modified_gmt":"2024-04-15T21:58:16","slug":"which-of-the-following-sentences-are-correct-in-reference-to-information-gain-a-it-is-biased-towards-single-valued-attributes-b-it-is-biased-towards-multi-valued-attributes-c-id3-makes-use-of-info","status":"publish","type":"post","link":"https:\/\/exam.pscnotes.com\/mcq\/which-of-the-following-sentences-are-correct-in-reference-to-information-gain-a-it-is-biased-towards-single-valued-attributes-b-it-is-biased-towards-multi-valued-attributes-c-id3-makes-use-of-info\/","title":{"rendered":"Which of the following sentences are correct in reference to Information gain? a. It is biased towards single-valued attributes b. It is biased towards multi-valued attributes c. ID3 makes use of information gain d. The approact used by ID3 is greedy"},"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_6a9786c9c8649\">\r\n                                            <div class=\"option\" data-option-key=\"option1\" data-is-correct=\"false\">\r\n                    a and b                <\/div>\r\n                                            <div class=\"option\" data-option-key=\"option2\" data-is-correct=\"false\">\r\n                    a and d                <\/div>\r\n                                            <div class=\"option\" data-option-key=\"option3\" data-is-correct=\"true\">\r\n                    b, c and d                <\/div>\r\n                                            <div class=\"option\" data-option-key=\"option4\" data-is-correct=\"false\">\r\n                    all of the above                <\/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>C. b, c and d<\/strong><\/p>\n<p>Information gain is a measure of how much information an attribute provides about the class of a data point. It is used in decision trees to select the best attribute to split on at each node.<\/p>\n<p>ID3 is a decision tree algorithm that uses information gain to select the best attribute to split on at each node. It is a greedy algorithm, which means that it always chooses the attribute that <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> provides the most information gain at each step, without considering the consequences of its choices later in the tree.<\/p>\n<p>Information gain is not biased towards single-valued or multi-valued attributes. It can be used with any type of attribute.<\/p>\n<p>The approach used by ID3 is greedy. This means that it always chooses the attribute that provides the most information gain at each step, without considering the consequences of its choices later in the tree. This can lead to suboptimal trees, but it is a simple and effective algorithm.<\/p>\n<p>Here is a more detailed explanation of each option:<\/p>\n<ul>\n<li><strong>a. It is biased towards single-valued attributes<\/strong><\/li>\n<\/ul>\n<p>This is not true. Information gain can be used with any type of attribute, including single-valued and multi-valued attributes.<\/p>\n<ul>\n<li><strong>b. It is biased towards multi-valued attributes<\/strong><\/li>\n<\/ul>\n<p>This is also not true. Information gain can be used with any type of attribute, including single-valued and multi-valued attributes.<\/p>\n<ul>\n<li><strong>c. ID3 makes use of information gain<\/strong><\/li>\n<\/ul>\n<p>This is true. ID3 is a decision tree algorithm that uses information gain to select the best attribute to split on at each node.<\/p>\n<ul>\n<li><strong>d. The approach used by <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> ID3 is greedy<\/strong><\/li>\n<\/ul>\n<p>This is also true. The approach used by ID3 is greedy. This means that it always chooses the attribute that provides the most information gain at each step, without considering the consequences of its choices later in the tree.<\/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>Which of the following sentences are correct in reference to Information gain? a. It is biased towards single-valued attributes b. It is biased towards multi-valued attributes c. ID3 makes use of information gain d. 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