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Hello there,
Thank you for the library and I'm enjoying using it.
I have a problem using myregressoradaptor with a simple linear regressor that is not sklearn.
let's say I have a very simple linear…
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https://github.com/sktime/sktime/blob/3c40420da9abfc64198a968a15870ce662c688c9/sktime/forecasting/base/_base.py#L598
Hi together,
every time I am trying to use one of the above functions, I get …
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Hi all
I'm new to the field. I would like to generate between 100 and 50 models for my target sequence to explore conformal flexibility of a specific region. This region is often (comparing predic…
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Hi,
I have read your paper and am interested in further exploring the IP_M function in my own conformal prediction studies.
I was wondering if you could give some more insight into the different m…
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It would be interesting to implement Conformalised Quantile Regression (Romano et al 2019) (https://arxiv.org/abs/1905.03222).
This could be done via the implementation of other Non-Conformity Measur…
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Following this paper : http://proceedings.mlr.press/v128/messoudi20a.html
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Classifiers have a `predict_proba` method that makes it possible to quantify probabilistic ally the certainty in the predictions for a given input `X_i`.
Currently most regressors in scikit-learn o…
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Great package. Is this approach adaptable for classification tasks?
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Dear Py-Boost developers,
Thanks for the very interesting paper and for making the code publicly available.
I am the author of [XGBoostLSS](https://github.com/StatMixedML/XGBoostLSS) and [Light…