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One practical way to review about 100 incorrect validation examples is to log them in a spreadsheet while examining them one by one and add short notes that help distinguish recurring failure patterns. A useful layout might include columns for Sample ID, Occluded Object, Motion Blur, Low Contrast, Wrong Label, and Comments.

Spreadsheet for Auditing Incorrect Validation Examples

Why build a spreadsheet while auditing misclassified validation examples?

Recording Errors During Model Review

The reviewer writes down _____ so specific cases can be recalled later.

Match each review-sheet field to what it records during error review.

Question:
In a concise analytical response, explain how examining roughly 120 misclassified validation photos, using category columns, and adding comments work together in this approach.

Sample answer:
The reviewer goes through about 120 validation photos that the model classified incorrectly and logs patterns in a spreadsheet. Category columns such as Occluded, Motion blur, Wrong label, and Hard lighting provide a shared checklist for marking what is true of each case. The comments column captures extra details that make individual examples easier to recall later. Used together, these fields let the reviewer summarize many errors without losing the context of any one example.

Key points:
- The reviewer inspects roughly 120 misclassified validation photos.
- Category columns create a consistent way to record patterns.
- Example categories include Occluded, Motion blur, Wrong label, and Hard lighting.
- Comments preserve specific notes about individual cases.

Rubric:
A strong response should explain the relationship among the approximate review count, the structured category fields, and the role of comments. It should stay grounded in the provided information and clearly show how the spreadsheet supports systematic error review.

Explain how a review spreadsheet organizes analysis of mislabeled validation photos.

Case context:
A reviewer is checking roughly 100 support tickets that a model assigned to the wrong class. The goal is to spot repeated error patterns without losing memorable details from individual tickets.

Question:
What is a good way to record the review, and which fields should the record include?

Sample answer:
Use a spreadsheet and update it during the review. Include columns such as Ticket ID, Billing issue, Shipping issue, Hard to read, Wrongly tagged, and Notes. The issue columns make it easy to compare patterns across tickets, and the Notes column preserves unusual details from specific cases.

Key points:
- Use a spreadsheet as the review log.
- Complete it while checking about 100 wrong predictions.
- Add columns for Ticket ID, Billing issue, Shipping issue, Hard to read, Wrongly tagged, and Notes.
- Use Notes for details that help you remember specific tickets.

Rubric:
The response should recommend a spreadsheet used during the review, name the supported fields, and explain the purpose of notes. Do not give full credit if the answer leaves out either the structured columns or the case-specific notes.

How a reviewer should log a set of misclassified support tickets.

Question:
Answer in one to three sentences: Why would a spreadsheet for reviewing misclassified dev-set examples include a Notes column?

Sample answer:
The Notes column lets the reviewer record observations tied to a particular example. It adds context that may not fit neatly into the category fields.

Key points:
- Notes capture example-specific observations.
- They provide extra context beyond the main labels.

Rubric:
A correct answer explains that the notes help preserve useful details about individual examples. Mentioning their value as extra context shows full understanding.

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