Construct · 1 fields · 1 citations

focal loss: a standalone construct

One name. One construct. A landmark on the map.

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Machine learning

a modified cross-entropy loss that down-weights well-classified examples so training concentrates on hard ones, countering extreme class imbalance in detection.

In machine learning, focal loss refers to a modified cross-entropy loss that down-weights well-classified examples so training concentrates on hard ones, countering extreme class imbalance in detection. This meaning comes from Lin (2017) in arXiv.[1]

Unit
Recovery means
Measured by

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Nearby constructs

class imbalance1 fields · 1 citationsanchor · a standalone construct class3 fields · 3 citationsjingle · one word, three constructs entropy6 fields · 12 citationsjingle · one name, six constructs

References

Lin, T., Goyal, P., Girshick, R., He, K., & Dollár, P. (2017). Focal Loss for Dense Object Detection. arXiv. https://doi.org/10.48550/arxiv.1708.02002

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