Re: [Scikit-learn-general] Gradient boosted regression trees: sparse matrix input

Thank you. I was however looking for whether the developers intend to implement sparse matrix support for GBRT On Sun, Aug 4, 2013 at 10:21 PM, Maheshakya Wijewardena < pmaheshak...@gmail.com> wrote: > As far I know. these are the only models that support sparse matrices > > linear_model.Logistic

Re: [Scikit-learn-general] Gradient boosted regression trees: sparse matrix input

2013/8/4 Maheshakya Wijewardena : > On Sun, Aug 4, 2013 at 7:34 PM, hrishi wrote: >> >> Are there any plans to implement sparse arrays for gradient boosted >> regression trees in scikit? Plans, yes, but no time. The recent refactoring of the trees module ought to have made this easier; a patch is

Re: [Scikit-learn-general] Gradient boosted regression trees: sparse matrix input

As far I know. these are the only models that support sparse matrices linear_model.LogisticRegression() svm.SVR() svm.NuSVR() linear_model.LinearRegression() neighbors.KNeighborsRegressor() naive_bayes.MultinomialNB() naive_bayes.BernoulliNB() linear_model.PassiveAggressiveRegressor() linear_model

[Scikit-learn-general] Gradient boosted regression trees: sparse matrix input

My data consists solely of categorical variables and I have used one hot encoding. I can't convert the sparse matrix to dense since I have too many categories. Are there any plans to implement sparse arrays for gradient boosted regression trees in scikit? -- Hrishikesh V. Ganu Mobile: 9740639