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The confusion matrix tells the truth faster — step 7 of 7

ch 41 · metrics, slices, and error analysisch 41 · metrics, slices, and error analysisch 41 · metrics, slices, and error analysisch 41 · metrics, slices, and error analysisch 41 · metrics, slices, and error analysisch 41 · metrics, slices, and error analysisch 41 · metrics, slices, and error analysisch 41 · metrics, slices, and error analysisch 41 · metrics, slices, and error analysisch 41 · metrics, slices, and error analysisch 41 · metrics, slices, and error analysis7/7
Checkpoint

One last thing before we move on. pass this to mark the lesson done, or skip and keep moving. hop to the next when you're ready.

Print the full labeled matrix for this eval — headers exactly as in the read step (" predicted 1 predicted 0" / "actual 1 TP=... FN=..." / "actual 0 FP=... TN=..."), then the accuracy line, then the makeup-detector line: "positive row mostly misses:" with whether FN > TP. An 80% accuracy whose actual-1 row is mostly FN is the majority-class baseline in disguise.

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