Thank you for the answer!!! I thought that this parameter just looks into my features? For example: weight, width, height... and so on.
Cause I'm using fingerprints as features, and every bit is a single feature (the fingerprints are about 2048 bits long). So i have for every fingerprints 2048 features. i thought about attributes like: Attributes: *estimators_* : list of DecisionTreeClassifier The collection of fitted sub-estimators. *classes_* : array of shape = [n_classes] or a list of such arrays The classes labels (single output problem), or a list of arrays of class labels (multi-output problem). *n_classes_* : int or list The number of classes (single output problem), or a list containing the number of classes for each output (multi-output problem). *feature_importances_* : array of shape = [n_features] The feature importances (the higher, the more important the feature). *oob_score_* : float Score of the training dataset obtained using an out-of-bag estimate. *oob_decision_function_* : array of shape = [n_samples, n_classes] Decision function computed with out-of-bag estimate on the training set. If n_estimators is small it might be possible that a data point was never left out during the bootstrap. In this case, oob_decision_function_ might contain NaN. Or am i wrong about this? On 27 May 2015 at 14:19, Arnaud Joly <a.j...@ulg.ac.be> wrote: > Hi, > > You can control the number of attributes that is drawn (tested) at each > node > with the max_features parameters. > > Best regards, > Arnaud Joly > > > > On 27 May 2015, at 11:47, Herbert Schulz <hrbrt....@gmail.com> wrote: > > > > Hello everyone, > > > > I'm using the "Random Forest Classifier" to predict the toxicity of a > compound. > > > > Is there a way to use an attribute selection with different set of > attributes for each tree node? > > > > I have this option in Knime, now I'm trying to implement it in python. > > > > I'll be very grateful for your help. > > > > best regards, > > > > Herb > > > ------------------------------------------------------------------------------ > > _______________________________________________ > > Scikit-learn-general mailing list > > Scikit-learn-general@lists.sourceforge.net > > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > > > > ------------------------------------------------------------------------------ > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >
------------------------------------------------------------------------------
_______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
