The Foundations of Cost-Sensitive Learning¶
Elkan, C. (2001). The Foundations of Cost-Sensitive Learning. Proceedings of the 17th International Joint Conference on Artificial Intelligence (IJCAI), 973-978.
Cited by¶
2 citations across 2 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Majority-Dominated Aggregate Objective
- Cost-sensitive learning's toolkit — reweighting, threshold-tuning, focal loss — transfers into surveillance-allocation reasoning
This sourceShows how class and misclassification-cost weighting shifts the optimal decision threshold, formalizing cost-sensitive reweighting for skewed distributions.
- Cost-sensitive learning's toolkit — reweighting, threshold-tuning, focal loss — transfers into surveillance-allocation reasoning
Mechanisms¶
- Confusion Audit
- Reading the raw volume of a confusion rather than its consequence over-invests in frequent-but-harmless swaps.
This sourceShows that confusion types should be evaluated by expected consequence, not raw frequency alone.
- Reading the raw volume of a confusion rather than its consequence over-invests in frequent-but-harmless swaps.
Verification¶
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Links previously used in the corpus¶
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