Free ISQI CT-AI_v1.0_World Exam Dumps Questions & Answers

A system was developed for screening the X-rays of patients for potential malignancy detection (skin cancer).
A workflow system has been developed to screen multiple cancers by using several individually trained ML models chained together in the workflow.
Testing the pipeline could involve multiple kind of tests (I - III):
I.Pairwise testing of combinations
II.Testing each individual model for accuracy
III.A/B testing of different sequences of models
Which ONE of the following options contains the kinds of tests that would be MOST APPROPRIATE to include in the strategy for optimal detection?
SELECT ONE OPTION

• A.Only II
• B.Only III
• C.I and III
• D.I and II

Pairwise testing can be used in the context of self-driving cars for controlling an explosion in the number of combinations of parameters.
Which ONE of the following options is LEAST likely to be a reason for this incredible growth of parameters?
SELECT ONE OPTION

• A.Different weather conditions
• B.Different features like ADAS, Lane Change Assistance etc.
• C.Different Road Types
• D.ML model metrics to evaluate the functional performance

Which ONE of the following combinations of Training, Validation, Testing data is used during the process of learning/creating the model?
SELECT ONE OPTION

• A.Training data - validation data
• B.Training data - validation data - test data
• C.Validation data - test data
• D.Training data * test data

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

Which ONE of the following tests is LEAST likely to be performed during the ML model testing phase?
SELECT ONE OPTION

• A.Testing the speed of the prediction by the model.
• B.Testing the accuracy of the classification model.
• C.Testing the API of the service powered by the ML model.
• D.Testing the speed of the training of the model.