Maybe you can also use bootstrap method published by Efron? You can see https://web.stanford.edu/~hastie/local.ftp/Springer/OLD/ESLII_print4.pdf
It is implemented in resampling module with replacement option, if I can understand. J. Dne 1.9.2016 21:46 napsal uživatel "Roman Yurchak" <[email protected]>: > I'm also interested to know if there are any projects similar to > scikit-learn-contrib/forest-confidence-interval for linear_model or SVM > regressors. > > In the general case, I think you could get a quick first order > approximation of the confidence interval for your regressor, if you take > the standard deviation of predictions obtained by fitting different > subsets of your data using, > cross_validation.cross_val_score( ).std() > with a fixed set of estimator parameters? Or some multiple of it (e.g. > 2*std). Though this will probably not match exactly the mathematical > definition of a confidence interval. > -- > Roman > > > On 01/09/16 20:32, Dale T Smith wrote: > > There is a scikit-learn-contrib project with confidence intervals for > random forests. > > > > https://github.com/scikit-learn-contrib/forest-confidence-interval > > > > > > ____________________________________________________________ > ______________________________ > > Dale Smith | Macy's Systems and Technology | IFS eCommerce | Data > Science and Capacity Planning > > | 5985 State Bridge Road, Johns Creek, GA 30097 | > [email protected] > > > > -----Original Message----- > > From: scikit-learn [mailto:scikit-learn-bounces+dale.t.smith= > [email protected]] On Behalf Of Daniel Seeliger via scikit-learn > > Sent: Thursday, September 1, 2016 2:28 PM > > To: [email protected] > > Cc: Daniel Seeliger > > Subject: [scikit-learn] Confidence Estimation for Regressor Predictions > > > > ⚠ EXT MSG: > > > > Dear all, > > > > For classifiers I make use of the predict_proba method to compute a Gini > coefficient or entropy to get an estimate of how "sure" the model is about > an individual prediction. > > > > Is there anything similar I could use for regression models? I guess for > a RandomForest I could simply use the indiviual predictions of each tree in > clf.estimators_ and compute a standard deviation but I guess this is not a > generic approach I can use for other regressors like the > GradientBoostingRegressor or a SVR. > > > > Thanks a lot for your help, > > Daniel > > _______________________________________________ > > scikit-learn mailing list > > [email protected] > > https://mail.python.org/mailman/listinfo/scikit-learn > > > > * This is an EXTERNAL EMAIL. Stop and think before clicking a link or > opening attachments. > > _______________________________________________ > > scikit-learn mailing list > > [email protected] > > https://mail.python.org/mailman/listinfo/scikit-learn > > > > _______________________________________________ > scikit-learn mailing list > [email protected] > https://mail.python.org/mailman/listinfo/scikit-learn >
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