The rows show “truth” the column show “test result.. Cell A has true positive sample

The rows show “truth” the column show “test result:

• A- Cell A has true positive sample.
• B- Cell A has true negative sample.
• C- Cell A has false positive sample.
• D- Cell A has false negative sample.

The answer is (a- Cell A has true positive sample).

Here's a breakdown of the concepts involved:

- Truth:

This refers to the actual, real-world state of a condition or attribute. It's the ground truth that we're trying to determine through a test.

- Test Result:

This is the outcome of a test or assessment that's designed to identify the presence or absence of the condition or attribute.

- Cells in a Confusion Matrix:

A confusion matrix is a table that visualizes the performance of a classification test. It typically has four cells:

• Cell A: True Positives (TP).
• Cell B: False Negatives (FN).
• Cell C: False Positives (FP).
• Cell D: True Negatives (TN).

Relation to cell A:

Here's how these terms relate to Cell A:

- True Positive:

A true positive in Cell A means that the test result correctly identified a sample as having the condition or attribute when it actually does have it. Both the truth and the test result are "positive" in this case.

- True Negative:

A true negative would be in Cell D, where the test result correctly identifies a sample as not having the condition or attribute when it actually doesn't.

- False Positive:

A false positive would be in Cell C, where the test result incorrectly identifies a sample as having the condition or attribute when it actually doesn't.

- False Negative:

A false negative would be in Cell B, where the test result incorrectly identifies a sample as not having the condition or attribute when it actually does.

Therefore, in the context of a confusion matrix where rows represent truth and columns represent test results, Cell A specifically holds the true positive samples.