[scikit-learn] 回覆： Using GPU in scikit learn

Hi, the scikit-learn random forest does not support GPUs.  If you want to do image classification using GPU processing, the standard way in this day and age is to use a neural network library like TensorFlow/keras or pytorch. GPUs can be faster than CPUs when the task is SIMD (single instruction

[scikit-learn] Fwd: BIC using GMM.fit and GaussianMixture.fit()

-- Forwarded message -- From: Dixeena Lopez Date: 2 August 2018 at 23:53 Subject: BIC using GMM.fit and GaussianMixture.fit() To: scikit-learn@python.org Dear Sir/Madam, I have tried to fit the data using GaussianMixture.fit() and GMM.fit() and calculated the BIC score. The BIC

Re: [scikit-learn] 回覆： Using GPU in scikit learn

Thank you very much for all of your information. Now I understand more about Scikit learn. On Thu, Aug 9, 2018 at 4:35 PM, blacklabel29 wrote: > Hi, > > > the scikit-learn random forest does not support GPUs. > > If you want to do image classification using GPU processing, the standard > way in

[scikit-learn] GMM.fit and GaussianMixture.fit()

Dear Sir/Madam, I have used GMM.fit() instead of GaussianMixture.fit() and got different answers. Please gives the advantage and disadvantage of these two. Please reply fast ‌Diixeena ___ scikit-learn mailing list scikit-learn@python.org https://mail.p

[scikit-learn] DBSCAN

Hi everyone, I'm trying to cluster 14000 samples using DBSCAN and want to know if there is a way to display the index of each data point along with it's label. I'm only able to access labels in the form of a list . When I look at the graph and see outliers (black points) , I'm not able to pin