Construct · 1 fields · 1 citations

out-of-distribution detection: a standalone construct

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Machine learning

flagging inputs that come from outside the training distribution, shown to be possible with a baseline using the classifier's maximum softmax probability.

In machine learning, out-of-distribution detection refers to flagging inputs that come from outside the training distribution, shown to be possible with a baseline using the classifier's maximum softmax probability. This meaning comes from Hendrycks (2016) in arXiv.[1]

Unit
Recovery means
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Nearby constructs

baseline2 fields · 2 citationsjingle · one word, two constructs distribution2 fields · 2 citationsjingle · one word, two constructs learning6 fields · 14 citationsjingle · one name, six constructs

References

Hendrycks, D., & Gimpel, K. (2016). A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks. arXiv. https://doi.org/10.48550/arxiv.1610.02136

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