[Scikit-learn-general] hmmlearn discussion list?

Hi, I know that HMM is not part of Scikit-learn anymore, and moved to another project called hmmlearn. But where can I go for any question regarding hmmlearn? ~ady -- Go from Idea to Many App Stores Faster with Intel(R)

Re: [Scikit-learn-general] ROC for one-class-SVM classifier

plt.show() … Best, Ady On 10/23/15, Ady Wahyudi Paundu <awpau...@gmail.com> wrote: > Hi Nicolas, Thank you for the pointer. > > Since i didn’t know where to take the value of ‘scoring’ variable, > this is what I did (by adapting to the example in scikit-learn web) > > …

Re: [Scikit-learn-general] ROC for one-class-SVM classifier

hresholds = roc_curve(y_true, scoring) > > # then you can plot(fpr, tpr) to get the roc curve and compute the AUC > with: > AUC = auc(fpr, tpr) > > ``` > > Best, > Nicolas > > 2015-10-20 3:41 GMT+02:00 Ady Wahyudi Paundu <awpau...@gmail.com>: > >> Hi

[Scikit-learn-general] ROC for one-class-SVM classifier

Hi all, Can I create ROC curve for one_class_SVM classifier? If I can, can you give pointer on how to do this? (or a link?) for example now i have: LD: normal data for learning (100 item) ND: normal data for evaluation (500 item) AD: abnormal data for evaluation (500 item) one_class_SVM code

Re: [Scikit-learn-general] Multiple normal scenario for one-class SVM

separately for the two models in the separate case? Btw, if you are modelling a single normal, maybe EllipticEnvelope would work better. Best, Andy On 08/04/2015 01:07 PM, Ady Wahyudi Paundu wrote: Hi all, How am I supposed to work with multiple set of normal data for one-class SVM? If I have

Re: [Scikit-learn-general] Multiple normal scenario for one-class SVM

that? On 08/04/2015 01:45 PM, Ady Wahyudi Paundu wrote: Hi Andy, thank you for the swift reply. No, for both case I was using the same set of parameters (nu and gamma = 0.01, kernel=rbf) Thank you for your suggestion, I will look into it. Regards, Ady On 8/5/15, Andreas Mueller

[Scikit-learn-general] Multiple normal scenario for one-class SVM

Hi all, How am I supposed to work with multiple set of normal data for one-class SVM? If I have two normal scenario data set, A and B for learning phase, should I create predictor model separately (M(A) + M(B)) or can I combine A and B to create just a single predictor model (M(A+B))? I have try

Re: [Scikit-learn-general] updating a model

Hi all, I found this paper on adaptive one-class SVM http://www.tsc.uc3m.es/~vanessa/publicaciones/articulos_revista/TSP_2011.pdf ~Ady -- ___ Scikit-learn-general mailing list

Re: [Scikit-learn-general] removing multicollinearity

Can I? I'm not that good in statistics, so I try it in R. Results from PCA and VIF were totally different ~ady On Sunday, April 12, 2015, Luca Puggini lucapug...@gmail.com wrote: Maybe you can try pca? On Sat, Apr 11, 2015, 18:24 Ady Wahyudi Paundu awpau...@gmail.com javascript:_e(%7B%7D

[Scikit-learn-general] removing multicollinearity

Hi all, In scikit-learn, how to pre-processing data and remove multicollinearity? ~Ady -- BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT Develop your own process in accordance with the BPMN 2 standard

Re: [Scikit-learn-general] updating a model

Thanks all, I am just thinking to build an anomaly (novelty) detector using one class SVM with manual inspection to detected anomaly as a feedback to update the normal model. i will think of something else :) Regards, AdyWP

[Scikit-learn-general] updating a model

Dear all, Suppose i have already fit a model, for example in one class SVM: clf = svm.OneClassSVM(nu=0.1, kernel=rbf, gamma=0.1) clf.fit(X_train) can i update the current fit (i.e.: clf) using new data? and how? Thanks, AdyWP