EMERGING TRENDS IN COMPUTING
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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The test error will keep getting smaller as the complexity of the model increases
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True
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False
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Either A or B
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None of the above
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Explanation:
Detailed explanation-1: -As the model complexity increases (x-direction), the training error decreases, and the test error increases. When the model is very complex, the gap between training and generalization/test error is very high. This is the state of overfitting.
Detailed explanation-2: -As the complexity of the model rises, the variance will increase and bias will decrease. In a simple model, there tends to be a higher level of bias and less variance. To build an accurate model, a data scientist must find the balance between bias and variance so that the model minimizes total error.
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