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confidence and credibility #19

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farzadhallaji opened this issue Jul 20, 2019 · 1 comment
Open

confidence and credibility #19

farzadhallaji opened this issue Jul 20, 2019 · 1 comment

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@farzadhallaji
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in

confidence = 1 - p.max(axis=1)

with due attention to http://www.quantware.ups-tlse.fr/ecoleluchon2015/slides/luo.pdf
compute the p-values p0 and p1 for both completions (with the tentative labels 0 and 1 for the new image, respectively);
• if p0 is smaller [intuitively, 0 is a stranger label than 1],
predict 1 with confidence 1 − p0 and credibility p1;
• if p1 is smaller [intuitively, 1 is a stranger label than 0],
predict 0 with confidence 1 − p1 and credibility p0.

must be changed to:
confidence = 1 - p.min(axis=1)

@patpizio
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I think this is managed by the previous lines of code.

The max values are set to -np.inf. At that point:

  • if you have 2 labels, p.max(axis=1) will actually be the minimum!
  • if you have more than 2 labels, p.max(axis=1) will return the second most likely label

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