Which of the following is an example of overfitting?

The correct answer is A. The model is not able to generalize to accommodate new types of data. Overfitting occurs when a machine learning (ML) model learns patterns that are too specific to the training data, leading to a lack of generalization for new, unseen data. This means the model performs exceptionally well on the training data but poorly on validation or test…

Machine Learning (ML)

Question

Options

AThe model is not able to generalize to accommodate new types of data.
BThe model is too simplistic for the data.
CThe model is missing relationships between the inputs and outputs.
DThe model discards data it considers to be noise or outliers.

How the community answered

(26 responses)

A
81% (21)
B
4% (1)
C
4% (1)
D
12% (3)

Explanation

Overfitting occurs when a machine learning (ML) model learns patterns that are too specific to the training data, leading to a lack of generalization for new, unseen data. This means the model performs exceptionally well on the training data but poorly on validation or test data because it has memorized the noise and minor details rather than learning the underlying patterns.

Topics

#overfitting#generalization#model training#underfitting

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