AI Associate AI Fundamentals Practice Question
A data scientist trains a churn prediction model on CRM data that includes customer tenure, support ticket count, and last purchase date. The model achieves 95% accuracy on training data but only 60% on a holdout validation set. What is the most likely issue?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The model is overfitting the training data
Large gap between training accuracy and validation accuracy is a classic sign of overfitting. The model memorized training data and fails to generalize.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The validation set contains data leakage
Why it's wrong here
Data leakage would likely cause validation accuracy to be artificially high, not low.
- ✗
The model needs more features
Why it's wrong here
More features could worsen overfitting; the core symptom points to overfitting.
- ✓
The model is overfitting the training data
Why this is correct
Correct: high training accuracy but much lower validation accuracy indicates overfitting.
- ✗
The model is underfitting the training data
Why it's wrong here
Underfitting would produce poor accuracy on both training and validation sets, not the observed 95% training accuracy with a sharp drop to 60% validation accuracy. This discrepancy indicates high variance, where the model memorises training noise rather than generalising. The option is tempting because underfitting is a common cause of low accuracy, but it specifically occurs when the model is too simple to capture underlying patterns, resulting in uniformly low performance across all datasets.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI Associate practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI Associate exam.