Which statement regarding the use of training, validation, and test data sets is correct?

The correct answer is D. The data in the test data set must be equivalent to the data in the training data sets and to the. The ISTQB CT-AI syllabus (Section3.2 - Model Evaluation) specifies the correct usage oftraining, validation, andtestdatasets. It emphasizes that the test dataset must be representative of the real operational dataand must beequivalent in distribution to the training and…

Machine Learning (ML)

Question

Options

AIf only limited data is available, validation and test data sets can be combined in multiple ways
BIf limited data is available, it may be better to work without a separate test data set.
COptimally, the data should be distributed equally between the training, validation, and test data
DThe data in the test data set must be equivalent to the data in the training data sets and to the

How the community answered

(55 responses)

A
4% (2)
B
9% (5)
C
16% (9)
D
71% (39)

Explanation

The ISTQB CT-AI syllabus (Section3.2 - Model Evaluation) specifies the correct usage oftraining, validation, andtestdatasets. It emphasizes that the test dataset must be representative of the real operational dataand must beequivalent in distribution to the training and validation sets, ensuring a fair and unbiased evaluation. Option D precisely matches this requirement.

Topics

#training data split#validation data#test data#cross-validation

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