AI Associate Data for AI Practice Question
A retail company has implemented a Salesforce AI lead scoring model to prioritize high-value customers. After three months, the model's AUC-ROC score is only 0.55, indicating poor performance. The data scientist reviews the training data and finds that 20% of the records are exact duplicates due to multiple data imports from different sources. The duplicates have inconsistent target labels (some labeled 'converted', others 'not converted'). What should the data scientist do to improve model performance?
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
✓
Remove all duplicate records and keep only one instance per duplicate group, resolving label conflicts by majority vote.
Duplicate records with conflicting labels confuse the model. Removing duplicates and resolving label conflicts (e.g., by majority vote) is the most effective step to clean the data and improve performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Downsample duplicates to reduce their impact but keep all records.
Why it's wrong here
Downsampling reduces but does not eliminate conflicting labels; the model will still learn incorrect patterns.
- ✗
Use the duplicates as a separate class to indicate noisy data.
Why it's wrong here
Treating duplicates as a separate class does not address the root cause and may distort the prediction task.
- ✓
Remove all duplicate records and keep only one instance per duplicate group, resolving label conflicts by majority vote.
Why this is correct
This cleans the data, removes noise, and provides consistent labels, likely improving model performance.
- ✗
Keep all duplicates because they represent multiple interactions; increase model complexity to handle them.
Why it's wrong here
Keeping duplicate with conflicting labels adds noise; increasing model complexity may lead to overfitting on noise.
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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.