Own python implementation of Random Forest classification algorithm
usage: run.py [-h] [--sample_frac] [--n_of_attrs] [--n_of_shrubs]
train_set classify_set class_col
positional arguments:
train_set training csv file with headers
classify_set unclassified csv file with headers
class_col class column header
optional arguments:
--sample_frac training data fraction per shrub (default .67)
--n_of_attrs number of attributes per shrub (default min(4, total number of attributes))
--n_of_shrubs number of shrubs (default 10)