Re: [scikit-learn] One-hot encoding

Hello, I have installed the dev version (0.20.dev0), should I just use Categorical Encoder or is the functionality already rolled up into OneHotEncoder. I get the following message: File "", line 1, in File "/scikit-learn/sklearn/preprocessing/data.py", line 2839, in *init* "CategoricalEncoder br

Re: [scikit-learn] One-hot encoding

Use OneHotEncoder ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] One-hot encoding

In the developer version, yes? Looking for the new memory savings :) On Wed, Aug 1, 2018, 17:29 Joel Nothman wrote: > Use OneHotEncoder > ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

[scikit-learn] pipeline for modifying target and number of samples

Hi, I posted a while back about this, and am reposting now since I have made progress on this topic. As you are probably aware, the sklearn Pipeline only supports transformers for X, and the number of samples must stay the same. I work with time series where the learning pipeline relies on

Re: [scikit-learn] pipeline for modifying target and number of samples

But you can't use cross_validate(seglearn.Pype(...), X, y) in general, can you, if the Pype changes the samples and their correspondence to the input y arbitrarily at both train and predict time? ​ ___ scikit-learn mailing list scikit-learn@python.org htt