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Build sklearn pipeline builder operations. Auto-activating skill for ML Training.
Passed 22 of 22 test cases with the skill, and 21 of 22 without it.
1 fixed21 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
I am writing a manual KFold cross-validation loop in Python. At each fold, I have train_idx and test_idx for DataFrame X and series y. How should a Pipeline instance `clf_pipeline` be fitted and evaluated inside each fold loop?
| Checked | Without skill | With skill |
|---|---|---|
| clf_pipeline.fit(X.iloc[train_idx], y.iloc[train_idx]) is called inside the loop. | Missed | Passed |
| clf_pipeline.predict or clf_pipeline.score is called on X.iloc[test_idx]. | Missed | Passed |
The instructions your model reads when the skill loads.
This skill provides automated assistance for sklearn pipeline builder tasks within the ML Training domain.
This skill activates automatically when you:
Example: Basic Usage Request: "Help me with sklearn pipeline builder" Result: Provides step-by-step guidance and generates appropriate configurations
test cases passed, vs 21 / 22 without
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