Now this isn't the best example, because joblib.Memory isn't going to be
very fast at dumping a list of strings, but I hope you can get the idea
from https://gist.github.com/jnothman/019d594d197c98a3d6192fa0cb19c850
On 17 August 2017 at 02:53, Georg Heiler wrote:
> Data cleaning @ enrichment
>
Data cleaning @ enrichment
Could you link an example for a mixing?
Currently this is a bit if a mess with custom pickle persistence in a big
for loop and custom transformers
Thanks.
Georg
Joel Nothman schrieb am Mi. 16. Aug. 2017 um 13:51:
> We certainly considered this over the many years tha
We certainly considered this over the many years that Pipeline caching has
been in the pipeline. Storing the fitted model means we can do both a
fit_transform and a transform on new data, and in many cases takes away the
pain point of CV over pipelines where downstream steps are varied.
What trans
There is a new option in the pipeline:
http://scikit-learn.org/stable/modules/pipeline.html#pipeline-cache
How can I use this to also store the transformed data as I only want to
compute the last step i.e. estimator during hyper parameter tuning and not
the transform methods of the clean steps?
Is
