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How do I implement custom evaluation metrics in scikit learn for a capstone project in my current Coursera data science certification?

ChatGPTgpt-61 query11/1/2026
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How do I implement custom evaluation metrics in scikit learn for a capstone project in my current Coursera data science certification?
1 real search · 1 real-search pass
scikit-learn official documentation make_scorer custom scoring callable classification metrics cross validationGoogle ↗
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Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.

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Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.

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Searches and sources

ChatGPT1 real searches · gpt-6
scikit-learn official documentation make_scorer custom scoring callable classification metrics cross validation Google ↗
  1. scikit-learn/doc/modules/model_evaluation.rst at main · scikit-learn/scikit-learn · github.com
  2. scikit-learn/doc/modules/cross_validation.rst at main · scikit-learn/scikit-learn · github.com
  3. 3.4. Metrics and scoring: quantifying the quality of predictions · scikit-learn.org

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Query / typeSearchIntentQuery classRouting formatClusterFreq ↓Weight
scikit-learn official documentation make_scorer custom scoring callable classification metrics cross validation
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