Inefficient since calling this method recursively copy outputs

Convert each feature vector into a row of predictions.

Every classifier in the ensemble votes for a class. If we're doing stacking, then pass the votes as features into the stacking

Extract all members from the archive to the current working directory and set owner, modification time and permissions on directories af

Download distribute from a specified location and return its filename `version` should be a valid distribute version number that is available

Will backup the file then patch it

get midpoints between all unique values

instead of returning output values, let the leaves fill an output matrix

Initialize partitions and leaf models to minimize training error

Install or upgrade setuptools and EasyInstall

A random forest is a bagging ensemble of randomized trees, so it can be implemented by combining the BaggedClassifier and RandomizedTree objects.

A random forest whose base classifier is a SVM-Tree (rather than splitting individual features we project each point onto a hyperplane) P