CT-AI 試験問題を無料オンラインアクセス

Which of the following is one of the reasons for data mislabelling?

• A.Small datasets
• B.Expert knowledge
• C.Lack of domain knowledge
• D.Interoperability error

Which supervised-learning classification/regression statement is correct?
Choose ONE option (1 out of 4)

• A.Deciding whether an object is a bicycle or a motorcycle is a classification problem
• B.Recognizing a dog from many different images is a regression problem
• C.Predicting that diesel prices will increase by ~10% is a classification problem
• D.In classification, objects are always assigned to exactly two classes

Which ONE of the following types of coverage SHOULD be used if test cases need to cause each neuron to achieve both positive and negative activation values?
SELECT ONE OPTION

• A.Neuron coverage
• B.Value coverage
• C.Sign change coverage
• D.Threshold coverage

A beer company is trying to understand how much recognition its logo has in the market. It plans to do that by monitoring images on various social media platforms using a pre-trained neural network for logo detection.
This particular model has been trained by looking for words, as well as matching colors on social media images. The company logo has a big word across the middle with a bold blue and magenta border.
Which associated risk is most likely to occur when using this pre-trained model?

• A.Insufficient function: the model was not trained to check for colors or words
• B.Improper data preparation
• C.There is no risk, as the model has already been trained
• D.Inherited bias: the model could have inherited unknown defects

Which statement about testing to prevent data poisoning and adversarial attacks is correct?
Choose ONE option (1 out of 4)

• A.Regression testing can be used to verify data sourcing policies to ensure the source of training data.
• B.Adversarial testing consists of using adversarial attacks to identify vulnerabilities so that they can be eliminated.
• C.Using AIB testing to identify data poisoning can better identify outliers than exploratory data analysis.
• D.The adversarial examples identified during adversarial testing must not be added to the training data so that they do not poison the model.