Feature Tracking Made Simple In Sklearn Transformers
blog.dailydoseofds.com
Recently, scikit-learn announced the release of one of the most awaited improvements. In a gist, sklearn can now be configured to output Pandas DataFrames. Until now, Sklearn's transformers were configured to accept a Pandas DataFrame as input. But they always returned a NumPy array as an output. As a result, the output had to be manually projected back to a Pandas DataFrame. This, at times, made it difficult to track and assign names to the features.
Feature Tracking Made Simple In Sklearn Transformers
Feature Tracking Made Simple In Sklearn…
Feature Tracking Made Simple In Sklearn Transformers
Recently, scikit-learn announced the release of one of the most awaited improvements. In a gist, sklearn can now be configured to output Pandas DataFrames. Until now, Sklearn's transformers were configured to accept a Pandas DataFrame as input. But they always returned a NumPy array as an output. As a result, the output had to be manually projected back to a Pandas DataFrame. This, at times, made it difficult to track and assign names to the features.