Re: [scikit-learn] Monthly meetings between core developers + "Hello World"
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! J ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
Re: [scikit-learn] Monthly meetings between core developers + "Hello World"
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! J ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
[scikit-learn] Predictive probability from cross_validate
Hi How to acquire the probability in the cross_validate function? Thanks Rujing -- 发自我的网易邮箱手机智能版 在 2019-08-05 22:31:38，"Andreas Mueller" 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! J ___ scikit-learn mailing list scikit-learn@python.orghttps://mail.python.org/mailman/listinfo/scikit-learn ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
Re: [scikit-learn] Monthly meetings between core developers + "Hello World"
Thanks everyone for joining, There's definitely room from improvement but this was still very productive I think :) The meeting notes are on the project board. I sent a google calendar invite to everyone for the next meeting: Monday 26th August, same time. If I missed you or if you want me to use another address, let me know. Anybody interested in moderating the next one? Nicolas On 8/5/19 10:31 AM, Andreas Mueller wrote: 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! J ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
[scikit-learn] Question about Kmeans implementation in sklearn
Dear Sklearn community, I have a simple question concerning the implementation of KMeans clustering algorithm. Two of the input arguments are the “n_init” and “random_state”. Consider a case where “n_init=10” and “random_state=0”. By looking at the source code (https://github.com/scikit-learn/scikit-learn/blob/1495f69242646d239d89a5713982946b8ffcf9d9/sklearn/cluster/k_means_.py#L187), we have the following: for it in range(n_init): # run a k-means once labels, inertia, centers, n_iter_ = kmeans_single( X, sample_weight, n_clusters, max_iter=max_iter, init=init, verbose=verbose, precompute_distances=precompute_distances, tol=tol, x_squared_norms=x_squared_norms, random_state=random_state) My question is: Why the results are not going to be the same for all `n_init` iterations since `random_state` is fixed? Bests, Makis ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
Re: [scikit-learn] Question about Kmeans implementation in sklearn
Hey Serafim, In this line https://github.com/scikit-learn/scikit-learn/blob/1495f69242646d239d89a5713982946b8ffcf9d9/sklearn/cluster/k_means_.py#L303 you can see that a randomstate object is constructed and that object is passed in the for loop that you are referring to, not the integer value that was passed in the function. Cheers, Chris On Mon, 5 Aug 2019 20:58 serafim loukas, wrote: > Dear Sklearn community, > > > I have a simple question concerning the implementation of KMeans > clustering algorithm. > Two of the input arguments are the “n_init” and “random_state”. > > Consider a case where *“n_init=10” and “random_state=0”.* > > By looking at the source code ( > https://github.com/scikit-learn/scikit-learn/blob/1495f69242646d239d89a5713982946b8ffcf9d9/sklearn/cluster/k_means_.py#L187), > we have the following: > > for it in range(n_init): > # run a k-means once > labels, inertia, centers, n_iter_ = kmeans_single( > X, sample_weight, n_clusters, max_iter=max_iter, init=init, > verbose=verbose, precompute_distances=precompute_distances, > tol=tol, x_squared_norms=x_squared_norms, > random_state=random_state) > > > My question is: Why the results are not going to be the same for all > `n_init` iterations since `random_state` is fixed? > > > Bests, > Makis > ___ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
