[scikit-learn] feature importance calculation in gradient boosting

Hi, I would like to understand how feature importances are calculated in gradient boosting regression. I know that these are the relevant functions: https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/ensemble/gradient_boosting.py#L1165 https://github.com/scikit-learn/scikit-learn

[scikit-learn] XGboost Classifier error

Hi!, I am trying to use XGBoost Classifer in RandomizedSearchCV as follows: clf = xgb.XGBClassifier() random_search_sg = RandomizedSearchCV(clf, param_distributions=params_dist, n_iter=n_iter_search, scoring=kappa_scorer,

Re: [scikit-learn] sklearn - knn sklearn.neighbors kneighbors function producing unexpected result for text analysis?

towards debugging, perhaps add the return_distances option On 16 Apr 2017 9:19 pm, "Evaristo Caraballo via scikit-learn" < scikit-learn@python.org> wrote: > I have been asked to implement a simple knn for text similarity analysis. > I tried by using sklearn.neighbors module. > The file to be anal