This is a random forest classifier developed for the course: INF01017 - Aprendizado de Máquina (2019/2).
This application requires Python version 3.6 or newer
There is a Makefile in the project folder which has set up rules for installing and running this application. Make sure you are on a python 3.6+ enviroment and call make setup.
main.py [-h] -d DATASET -a ATTRIBUTES [-s SEED] [-m M] [-n NTREE] [-k KFOLDS] [-p] [-v]
Random Forest Classifier
mandatory arguments:
-d DATASET, --dataset DATASET
Path to csv dataset for training or classification.
-a ATTRIBUTES, --attributes ATTRIBUTES
Path to json object containing attributes wich will be
used and its kind information.
optional arguments:
-h, --help show this help message and exit
-s SEED, --seed SEED Seed to random numbers and sampling.
-m M Number of sample attributes used on each division on
tree [if not present, all attributes are used].
-n NTREE, --ntree NTREE
Number of trees generated on ensamble [default: 5].
-k KFOLDS, --kfolds KFOLDS
Number of k-folds generated for cross-validation
[default: 5].
-p, --parallelize Parallelize with 2x number of cpu cores processes on
tree generation. WARNING: seed values wont work if -p
activated.
-v, --verbose