Hi,
I am using random forest classifier and this algorithm train a tree defined
as :
DecisionTreeClassifier(criterion='gini', max_depth=None,
max_features='auto',
max_leaf_nodes=None, min_samples_leaf=1, min_samples_split=2,
min_weight_fraction_leaf=0.0, random_state=1982007276,
splitter='best')]
I do not understand what algorithm is used to train a tree with this
parameters.
Is there any reference that describes the used training algorithm in
details?
In particular I do not understand the split strategy
splitter : string, optional (default="best")
The strategy used to choose the split at each node. Supported strategies
are "best" to choose the best split and "random" to choose the best random
split.
Thanks for help,
Luca
------------------------------------------------------------------------------
Want excitement?
Manually upgrade your production database.
When you want reliability, choose Perforce
Perforce version control. Predictably reliable.
http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk
_______________________________________________
Scikit-learn-general mailing list
Scikit-learn-general@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
