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.PassiveAggressiveClassifier()
linear_model.Perceptron()
linear_model.Ridge()
linear_model.Lasso()
linear_model.ElasticNet()
On Sun, Aug 4, 2013 at 7:34 PM, hrishi <[email protected]> wrote:
> 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: 9740639172
> http://in.linkedin.com/pub/hrishikesh-ganu/5/5a7/773
>
>
>
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