[[["সহজে বোঝা যায়","easyToUnderstand","thumb-up"],["আমার সমস্যার সমাধান হয়েছে","solvedMyProblem","thumb-up"],["অন্যান্য","otherUp","thumb-up"]],[["এতে আমার প্রয়োজনীয় তথ্য নেই","missingTheInformationINeed","thumb-down"],["খুব জটিল / অনেক ধাপ","tooComplicatedTooManySteps","thumb-down"],["পুরনো","outOfDate","thumb-down"],["অনুবাদ সংক্রান্ত সমস্যা","translationIssue","thumb-down"],["নমুনা / কোড সংক্রান্ত সমস্যা","samplesCodeIssue","thumb-down"],["অন্যান্য","otherDown","thumb-down"]],["2025-02-25 UTC-তে শেষবার আপডেট করা হয়েছে।"],[[["\u003cp\u003eThis page provides multiple-choice exercises focused on overfitting and pruning in decision trees.\u003c/p\u003e\n"],["\u003cp\u003eThe exercises cover topics like the impact of leaf size on tree structure and techniques to reduce overfitting in decision tree models.\u003c/p\u003e\n"]]],[],null,["\u003cbr /\u003e\n\nThis page challenges you to answer a series of multiple choice exercises\nabout the material discussed in the \"Overfitting and pruning\" unit.\n\nQuestion 1 \nWhat are the two potential effects of increasing the minimum number of examples per leaf in a decision tree? \nThe size of the decision tree increases. \nThe size of the decision tree decreases. \nWell done. \nThe structure of the decision tree can completely change. \nThe structure of the decision tree remains mostly unchanged. \nWell done.\n\nQuestion 2 \nWhat operations can reduce overfitting in a model known to be overfitted (for example, by evaluating it on a test dataset). \nIncrease the maximum depth. \nDecrease the maximum depth. \nIncrease the minimum number of observations in the leaves. \nDecrease the minimum number of observations in the leaves. \nIncrease the minimum gain of a new node. \nDecrease the minimum gain of a new node."]]
