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CT-AI · Question #97

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…

The correct answer is B. I and II. The question asks which combination of tests would be most appropriate to include in the strategy for optimal detection in a workflow system using multiple ML models. Pairwise testing of combinations (I): This method is useful for testing interactions between different…

Test Strategies for AI-based Systems

Question

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?

Options

  • AOnly III
  • BI and II
  • CI and III
  • DOnly II

How the community answered

(62 responses)
  • A
    15% (9)
  • B
    74% (46)
  • C
    6% (4)
  • D
    5% (3)

Explanation

The question asks which combination of tests would be most appropriate to include in the strategy for optimal detection in a workflow system using multiple ML models. Pairwise testing of combinations (I): This method is useful for testing interactions between different components in the workflow to ensure they work well together, identifying potential issues in the integration. Testing each individual model for accuracy (II): Ensuring that each model in the workflow performs accurately on its own is crucial before integrating them into a combined workflow. A/B testing of different sequences of models (III): This involves comparing different sequences to determine which configuration yields the best results. While useful, it might not be as fundamental as pairwise and individual accuracy testing in the initial stages.

Topics

#ML pipeline testing#pairwise testing#model accuracy#chained models

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