2012/11/12 <[email protected]>: > > Dear SciKitters, > > given an array of (n_samples,n_features) -> How do I assign target_names in > a concluding step? > > The target_names are stored in a list and, of course, have the same order > as the n_features vector. > > In a next step, I would like to dump out the importance of the most > relevant features? How can this be done in scikit-learn? In particular, I > have trained a random forest and would like to dump out the leaves of this > RF.
Hi Paul, this example shows how to access the feature importance computed by a RF:: http://scikit-learn.org/stable/auto_examples/ensemble/plot_forest_importances.html#example-ensemble-plot-forest-importances-py in order to access the ``feature_importances_`` attribute you have to use the following argument ``compute_importances=True`` . To access the leaves of a decision tree you need to access the ``tree_`` attribute of a DecisionTree - it is basically a collection of parallel arrays that represent the tree (see sklearn.tree._tree). All indices where ``children_left`` and ``children_right`` is -1 are leaves. best, Peter > > > Cheers & Thanks, > Paul > > This message and any attachment are confidential and may be privileged or > otherwise protected from disclosure. If you are not the intended recipient, > you must not copy this message or attachment or disclose the contents to > any other person. If you have received this transmission in error, please > notify the sender immediately and delete the message and any attachment > from your system. Merck KGaA, Darmstadt, Germany and any of its > subsidiaries do not accept liability for any omissions or errors in this > message which may arise as a result of E-Mail-transmission or for damages > resulting from any unauthorized changes of the content of this message and > any attachment thereto. Merck KGaA, Darmstadt, Germany and any of its > subsidiaries do not guarantee that this message is free of viruses and does > not accept liability for any damages caused by any virus transmitted > therewith. > > Click http://www.merckgroup.com/disclaimer to access the German, French, > Spanish and Portuguese versions of this disclaimer. > > > ------------------------------------------------------------------------------ > Everyone hates slow websites. So do we. > Make your web apps faster with AppDynamics > Download AppDynamics Lite for free today: > http://p.sf.net/sfu/appdyn_d2d_nov > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general -- Peter Prettenhofer ------------------------------------------------------------------------------ Everyone hates slow websites. So do we. Make your web apps faster with AppDynamics Download AppDynamics Lite for free today: http://p.sf.net/sfu/appdyn_d2d_nov _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
