On 10/05/2018 12:00 PM, Kevin Markham wrote:
Hello all,
Congratulations on the release of 0.20! My questions are about the
updated classification_report:
http://scikit-learn.org/stable/modules/generated/sklearn.metrics.classification_report.html
Here is the simple example shown in the
A lot of this is discussed in
http://scikit-learn.org/dev/modules/model_evaluation.html
If you passed only a limited set of labels in, micro average would not
necessarily be identical across P/R/F. This allows for a "negative label",
often an experimentally uninteresting majority class.
Try
Hello all,
Congratulations on the release of 0.20! My questions are about the updated
classification_report:
http://scikit-learn.org/stable/modules/generated/sklearn.metrics.classification_report.html
Here is the simple example shown in the documentation (apologies for the
formatting):
>>> from
