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p-lambda
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verified_calibration
Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlight).
MIT License
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When a bin has samples of the same probability
#19
forrestbao
opened
3 months ago
0
The number orders are not consistent before/after calibration
#18
Miaoranmmm
closed
7 months ago
2
Function parameter not used
#17
filipchristiansen
opened
1 year ago
0
Undefined variable
#16
filipchristiansen
opened
1 year ago
0
Unused variable
#15
filipchristiansen
opened
1 year ago
0
Incorrect type hints
#14
filipchristiansen
opened
1 year ago
0
Bootstrap uncertainty details
#13
e-pet
opened
1 year ago
1
Changes sklearn requirement to scikit-learn
#12
yifanmai
closed
1 year ago
0
Incorrect scikit-learn package requirement
#11
yifanmai
closed
1 year ago
0
Error if a bin has only a single class in it
#10
zacps
opened
2 years ago
0
added wrapper function in utils.py for getting accuracy of bins
#9
sdelcore
opened
3 years ago
1
Allow missing classes for softmax input
#8
mpitropov
closed
3 years ago
1
Calculate calibration error with softmax distribution and missing class
#7
mpitropov
closed
3 years ago
0
Calibrated probabilites from "top" calibrators
#6
Tuyki
closed
3 years ago
1
Pickle trained Calibrators
#5
sudhanshu22gupta
closed
3 years ago
4
Reproducing Figure 3 of the paper
#4
shgoshtasb
closed
3 years ago
3
Question: Reliability diagrams
#3
mpitropov
closed
3 years ago
3
Unable to obtain calibration error when missing a class
#2
mpitropov
closed
3 years ago
2
Question about num_calibration
#1
TortoiseHam
closed
3 years ago
2