[scikit-learn] Predictive probability from cross_validate

charujing123 charujing123 at 163.com
Mon Aug 12 22:13:02 EDT 2019

 this function is exactly what i wanted. However, the description of this function contained this: Passing these predictions into an evaluation metric may not be a valid way to measure generalization performance. 
Could i use this prediction to calculate the accuracy? I am not sure after seeing this sentence.



发件人:Guillaume Lemaître <g.lemaitre58 at gmail.com>
发送时间:2019-08-12 23:16
主题:Re: [scikit-learn] Predictive probability from cross_validate
收件人:"Scikit-learn mailing list"<scikit-learn at python.org>

cross_validate should not be used to make predictions but to evaluate the performance, the parameter, etc of models.
You probably want to check cross_val_predict to get the prediction. However, be aware of what it involves:

On Mon, 5 Aug 2019 at 16:57, Rujing Zha <charujing123 at 163.com> wrote:

How to acquire the probability in the cross_validate function?


在 2019-08-05 22:31:38,"Andreas Mueller" <t3kcit at gmail.com> 写道:

As usual, I agree ;)
I think it would be good to call out particularly important bugfixes so they get reviews.
We might also want to think about how we can organize the issue tracker better.

Having more full-time people on the project certainly means more activity but ideally we can use some of that time to make the issue tracker more organized.

On 8/5/19 9:21 AM, Joel Nothman wrote:

Yay for technology! Awesome to see you all and have some matters clarified. 

Adrin is right that the issue tracker is increasingly overwhelming (because there are more awesome people hired to work on the project, more frequent sprints, etc). This meeting is a useful summary.

The meeting mostly focussed on big features. We should be careful to not leave behind important bugs fixes and work originating outside the core devs.

Despite that: Some of Guillaume's activities got cut off. I think it would be great to progress both on stacking and resampling before the next release.

I also think these meetings should, as a standing item, note the estimated upcoming release schedule, to help us remain aware of that cadence.

Good night!


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Guillaume Lemaitre
INRIA Saclay - Parietal team
Center for Data Science Paris-Saclay
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