Which ONE of the below is MOST likely to indicate a problem with underfitting in an ML model?

The correct answer is D. The model is inaccurate on data similar to the training data. Underfitting occurs when the model is too simplistic to capture the underlying patterns in the training data. This results in poor performance not only on new data but also on the data it was trained on. Thus, if the model is inaccurate on data similar to the training data, it…

Machine Learning (ML)

Question

Options

AThe model is vulnerable to adversarial attacks
BThe model fails to generalize on new data
CThe model uses a large amount of resources to make a prediction
DThe model is inaccurate on data similar to the training data

How the community answered

(28 responses)

A
7% (2)
B
11% (3)
C
4% (1)
D
79% (22)

Explanation

Underfitting occurs when the model is too simplistic to capture the underlying patterns in the training data. This results in poor performance not only on new data but also on the data it was trained on. Thus, if the model is inaccurate on data similar to the training data, it suggests

Topics

#underfitting#model accuracy#overfitting#generalization

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