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[`impute_capital_gains`](https://github.com/PolicyEngine/policyengine-uk/blob/f89baee294f74990c26f024cdb32125610169b38/policyengine_uk/data/datasets/frs/imputations/capital_gains.py#L41) currently int…
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Hi, thank you for this project!
I am trying to figure out - can we do smth to solve crossing problem? I mean when for example 49th quantile is more than 50th.
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### Describe the workflow you want to enable
In addition to `method="sigmoid"` and `method="isotonic"` it would be great to pass any scikit-learn compatible classifier with a `predict_proba` to `Ca…
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Thanks for the work on this! Here's an example:
```python
import jax.numpy as jnp
from fast_soft_sort.jax_ops import soft_rank
from jax import grad, jit
@jit
def f1(x):
x = x.reshape(1,…
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# Code sample
Taking a look at the return logs of the learners, e.g. the logistic regression one:
```python
log = {'logistic_classification_learner': {
'features': features,
…
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ニューラルモデルのstructured predictionにおけるCalibrationにおいては通常の isotonic regressionやtemperature scalingがそのままでは適用できない。この論文で提案するensemble distillationは予測精度を落とさずにCalibrationを実現する。
https://www.aclweb.org/anthology/…
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Classifiers in this note refer to:
- algorithmic such as SVM or Random Forests. In this case the scikit `predict_proba` function is sometimes used as a measure of confidence
- Neural Networks such…
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### Describe the workflow you want to enable
```python
import numpy as np
from sklearn.calibration import calibration_curve
y_true = np.array([0, 0, 0, 0, 1, 1, 1, 1, 1])
y_pred = np.array([0…
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Usually, classification algorithms return 0 or 1 value, thus mapping a specimen to either class.
In our case, however, we want to get probability that a sensor is good / bad.
The challenge is to custo…
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### Describe the workflow you want to enable
### Proposition
I'd like to decompose scores (at least the ones from consistent scoring functions for identifiable functionals) into meaningful additiv…