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Model Evaluation Techniques Quiz

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Questions and Answers

Why is it not recommended to use the same data to evaluate a model that was used to train it?

The model will generalize well on unseen data

The model will overfit and memorize the training data (correct)

The model will suffer from underfitting

The model will make unbiased predictions

Which term describes the process of understanding the reliability of an AI model by comparing its outputs with actual answers?

Model Verification

Model Validation

Model Generation

Model Evaluation (correct)

What is a common risk associated with evaluating a model solely based on its performance on the training dataset?

Model will easily adapt to new scenarios

Model will have high accuracy on unseen data

Model will underfit the training data

Model will overfit and fail to generalize well (correct)

What does underfitting in a model indicate?

The model's accuracy is lower and it fails to capture the true function (A) Signup and view all the answers

How is overfitting in a model defined?

The model is trying to cover all the data samples even if they are out of alignment to the true function (D) Signup and view all the answers

Why is evaluating AI models important?

To understand the efficiency and accuracy of the model (A) Signup and view all the answers

Why is Precision considered an important evaluation criteria for models?

Precision helps in reducing false alarms and increasing true positive cases. (C) Signup and view all the answers

What does high Precision imply about a model's performance?

High Precision indicates more true positive cases and fewer false alarms. (A) Signup and view all the answers

In the context of the text, what might happen if Precision is low?

There will be more false alarms than actual fires. (B) Signup and view all the answers

Why is good Precision not equivalent to good model performance?

Good Precision can lead to complacency and missed opportunities. (C) Signup and view all the answers