Lorenzo

An algorithm iteratively learns how to classify data by maximising the accuracy of its performance. However, what would likely happen when the dataset is highly unbalanced (e.g., 99% of positives and 1% of negatives)?

• the algorithm is not able to learn because the accuracy will always stay too low (~0.01)

• the algorithm is not able to learn because the accuracy will always stay too high (~0.99)

• accuracy is never related to the balancement of the classes

• I don't know

An algorithm iteratively learns how to classify data by maximising the accuracy of its performance. However, what would likely happen when the dataset is highly unbalanced (e.g., 99% of positives and 1% of negatives)?

• the algorithm is not able to learn because the accuracy will always stay too low (~0.01)

• the algorithm is not able to learn because the accuracy will always stay too high (~0.99)

• accuracy is never related to the balancement of the classes

• I don't know

You are developing a model for sick patient detection (sick=positive, healthy=negative). Which metric would you use?

• Accuracy

• Precision

• Recall

• I don't know

You are developing a model for sick patient detection (sick=positive, healthy=negative). Which metric would you use?

• Accuracy

• Precision

• Recall

• I don't know

You are developing a model for email spam detection (spam=positive, non-spam=negative). Which metric would you use?

• Accuracy

• Precision

• Recall

• I don't know

You are developing a model for email spam detection (spam=positive, non-spam=negative). Which metric would you use?

• Accuracy

• Precision

• Recall

• I don't know

You are developing a model for fraudolent transaction detection (fraudolent=positive, non-fraudolent=negative). Which metric would you use?

• Accuracy

• Precision

• Recall

• I don't know

You are developing a model for fraudolent transaction detection (fraudolent=positive, non-fraudolent=negative). Which metric would you use?

• Accuracy

• Precision

• Recall

• I don't know

Which model would you choose?

• A

• B

• I don't know

Which model would you choose?

• A

• B

• I don't know