题目
STATISTICAL DEEP LEARNING DONE_2025 Mid-term Close-book Exam
多项填空题
Choose from: overfitting, or underfitting: 1) If your model cannot even fit the training examples, then you have large bias. For this case, which fitting does it belong to: [Fill in the blank], ; 2) If you can fit the training data, but large error on testing data, then you probably have large variance. For this case, which fitting does it belong to: [Fill in the blank], ;
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标准答案
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思路分析
The question asks you to classify two scenarios using the terms related to bias and variance in model fitting, specifically where each scenario fits best: underfitting or overfitting.
First, consider the situation described in item 1: a model that cannot even fit the training examples. When a model performs poorly on the training data, it indicates high bias: the model is too simple or wrong in its assumptions to capture the underlying patterns. This scenario corresponds to underfitting, not overfitting, because overfitting would mani......Login to view full explanation登录即可查看完整答案
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Question at position 19 Select ALL the answers that are correct: When using a classifier, increasing the complexity of the model Note: To calculate scores for Multiple Answers questions such as this one, Canvas divides the total points possible by the amount of correct answers for that question. This amount is awarded for every correct answer selected and deducted for every incorrect answer selected. Hence, it is best to choose only the answers you are certain that they are correct (otherwise Canvas will deduct points for incorrect answers you select). may either increase or decrease the training errorwill generally increase the testing errormay either increase or decrease the testing errorwill generally increase the training errorwill generally decrease the testing errorwill generally decrease the training error
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