A healthcare company experiences a cyberattack, where the hackers were able to reverse-engineer a dataset to break confidentiality.
Which of the following is TRUE regarding the dataset parameters?
A . The model is overfitted and trained on a high quantity of patient records.
B . The model is overfitted and trained on a low quantity of patient records.
C . The model is underfitted and trained on a high quantity of patient records.
D . The model is underfitted and trained on a low quantity of patient records.
Answer: B
Explanation:
Overfitting is a problem that occurs when a model learns too much from the training data and fails to generalize well to new or unseen data. Overfitting can result from using a low quantity of training data, a high complexity of the model, or a lack of regularization. Overfitting can also increase the risk of reverse-engineering a dataset from a model’s outputs, as the model may reveal too much information about the specific features or patterns of the training data. This can break the confidentiality of the data and expose sensitive information about the individuals in the dataset.
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