Each tree is built using a random sample with replacement from the provided
training data. The data not in the sample is used to calculate the out-of-bag
score. The “bag” is the sampled data.
The “random” refers to several features of the algorithm, including random
sampling of features
So for each tree
Get a random sample of the training data
For I to n_estimators:
Build a tree – this involves a random sample of
features and thresholds for each feature in the sample at each node.
Use the rest of the training data, not in the
sample, to calculate the out-of-bag score
Random Forest already incorporates “random features”.
https://github.com/glouppe/phd-thesis
__________________________________________________________________________________________
Dale Smith | Macy's Systems and Technology | IFS eCommerce | Data Science
770-658-5176 | 5985 State Bridge Road, Johns Creek, GA 30097 |
[email protected]
From: scikit-learn
[mailto:[email protected]] On Behalf Of ??
Sent: Tuesday, September 13, 2016 4:16 AM
To: [email protected]
Subject: [scikit-learn] is RandomForest random samples or random features?
⚠ EXT MSG:
I have read the Guide of sklearn's RandomForest :
"""
In random forests (see
RandomForestClassifier<http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html#sklearn.ensemble.RandomForestClassifier>
and
RandomForestRegressor<http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html#sklearn.ensemble.RandomForestRegressor>
classes), each tree in the ensemble is built from a sample drawn with
replacement (i.e., a bootstrap sample) from the training set.
"""
But I prefer RandomForest as :
"""
features ("attributes", "predictors", "independent variables") are randomly
sampled
"""
is RandomForest random samples or random features? where can I find a features
random version of RandomForest?
thx.
* This is an EXTERNAL EMAIL. Stop and think before clicking a link or opening
attachments.
_______________________________________________
scikit-learn mailing list
[email protected]
https://mail.python.org/mailman/listinfo/scikit-learn
