Re: [scikit-learn] intermediate data state in a Pipeline

Using slicing: model[:-1].transform(X) Sent from my iPhone > On 11 Apr 2022, at 20:24, Sole Galli via scikit-learn > wrote: > >  > Hello community, > > Say I have a pipeline with 3 data transformations, i.e., SimpleImputer, > OrdinalEncoder and StandardScaler, and a Lasso at the end. And I

[scikit-learn] intermediate data state in a Pipeline

Hello community, Say I have a pipeline with 3 data transformations, i.e., SimpleImputer, OrdinalEncoder and StandardScaler, and a Lasso at the end. And I want to obtain a copy of the transformed data that would be input to the Lasso. Is there a way other than selecting all the steps of the pipe

[scikit-learn] CFP LivingNER shared task: Named entity recognition, normalization & classification of species, pathogens and food

Call for Participation LivingNER Shared Task (IberLEF2022) Named entity recognition, normalization & classification of species, pathogens and food https://temu.bsc.es/livingner/ LivingNER is the first track focusing specifically on the automatic detection of species mentions (humans, plants,