COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Model which overfit has high bias and high variance
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Model which overfits have Low bias and low variance
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Model which overfits has high Bias and Low variance
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Model which overfits has low Bias and High Variance
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Detailed explanation-1: -Answer. Answer: Underfitted models have high bias . Overfitted models have high variance.
Detailed explanation-2: -Underfitted models have low bias ( false ). Overfitted models have high variance ( true ). Overfitted models have low variance ( false ).
Detailed explanation-3: -Specifically, overfitting occurs if the model or algorithm shows low bias but high variance. Overfitting is often a result of an excessively complicated model, and it can be prevented by fitting multiple models and using validation or cross-validation to compare their predictive accuracies on test data.
Detailed explanation-4: -Bias and Variance Trade-off In underfitting, our model is too simple and has very few variables then it may have high bias. On the other hand, in overfitting, our model has more number of independent variables then it will results in high variance and low bias.