Exam CT-AI Topic 10 Question 123 Discussion

Actual exam question for ISTQB's CT-AI exam
Question #: 123
Topic #: 10

Which of the following options is an example of the concept of overfitting?

A. A model for predicting academic performance was trained with data from students at one university. The model shows low predictive accuracy when applied to other universities. B. A model for the recognition of dogs was trained predominantly with pictures of dogs in parks. On pictures with other animals in parks, dogs are also falsely recognized. C. A previously trained model for recognizing cars is adapted and extended so that it can also identify the make of the car beyond its original function. D. A model for predicting IT system failures delivers too many false-negative predictions because the failures cannot be adequately explained via the log files used for training.

Suggested Answer: A Vote an answer

The ISTQB CT-AI syllabus defines overfitting in Section3.2 - ML Model Evaluationas a condition where an ML model learns the training data too precisely--including noise and irrelevant detail-- resulting in poor performance on unseen data. Overfitting is characterized byhigh accuracy on training data but low accuracy on validation or real-world data. Option A perfectly matches this definition: a model trained only on one university's student data generalizes poorly to students from other universities.
This is a textbook example of overfitting because the model has essentially memorized patterns unique to a narrow dataset, instead of learning generalizable relationships applicable across environments .

by Bennett at Apr 27, 2026, 07:42 AM

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