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 wrote: > Maybe you can try pca? > > On Sat, Apr 11, 2015, 18:24 Ady Wahyudi Paundu > wrote: > >> Hi all, >> >> In scikit-learn, how to pre-proc

Re: [Scikit-learn-general] removing multicollinearity

Maybe you can try pca? On Sat, Apr 11, 2015, 18:24 Ady Wahyudi Paundu wrote: > Hi all, > > In scikit-learn, how to pre-processing data and remove multicollinearity? > > ~Ady > > > -- > BPM Camp - Free Virtual Workshop Ma

[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 Learn

Re: [Scikit-learn-general] GSoC 2015: Semi-supervised learning proposal

I've made some changes to the proposal. https://github.com/scikit-learn/scikit-learn/wiki/GSoC-2015-Proposal:-scikit-learn:-Cross-validation-and-Meta-estimators-for-Semi-supervised-learning On Wed, Apr 8, 2015 at 8:44 PM, Andreas Mueller wrote: > So what would you sugggest? > > On 04/07/2015 08:

Re: [Scikit-learn-general] adaboost parameters

What is your dataset like? How are you building your individual classifier that you are ensembling with AdaBoost? A common-use case would be boosted decision stumps (one-level decision trees). http://en.wikipedia.org/wiki/Decision_stump http://lyonesse.stanford.edu/~langley/papers/stump.ml92.pd

Re: [Scikit-learn-general] Micro and Macro F-measure for text classification

Or report macro and micro in classification_report. Micro is equivalent to accuracy for multiclass without #4287 . On 10 April 2015 at 01:00, Andreas Mueller wrote: > Hi Jack. > You mean in the classification report? > That give micro-aver