Data files are generated using the ISCX generator.
python -m virtualenv env
source env/bin/activate
pip install -r requirements.txt
Main file to launch for the challenge.
python defi.py
-h, --help show this help message and exit
-r Index files to ElasticSearch and exit the program.
Files must be indexed before working with classifiers.
--index INDEX Name of the ElasticSearch index to use.
default: "flow"
--dir_train DIR_TRAIN
Directory to load the XML training file(s) from.
This directory contain the file(s) used for the training.
It shouldn't contain any file with unknown tag.
default: "./defi_train"
--dir_test DIR_TEST Directory to load the XML test file(s) from.
This directory contain the file(s) used for the test.
default: "./defi_test"
--output OUTPUT Name of the output file containing the results.
default: "output"
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Index files to ElasticSearch index "defi" from directories "train/" and "test/" containing training files and test files:
python defi.py -r --index defi --dir_train train --dir_test test
-
Train and classify test flows from index "defi" and print results to "results.txt" file:
python defi.py --index defi --output results.txt
Main file we used for the project. Its main use is to facilitate the comparison of different classifier.
python main.py
-h, --help show this help message and exit
-r Index files to ElasticSearch and exit the program.
Files must be indexed before working with classifiers.
--index INDEX Name of the ElasticSearch index to use.
default: "flow"
--dir DIR Directory to load the XML file(s) from.
This directory contain the file(s) used for the classification.
default: "./ISCX_train"
Display a Zipf diagram.
python zipf.py
-h, --help show this help message and exit
-r Index files to ElasticSearch and exit the program.
Files must be indexed before working with classifiers.
--index INDEX Name of the ElasticSearch index to use.
default: "flow"
--dir DIR Directory to load the XML file(s) from.
This directory contain the file(s) used for the classification.
default: "./ISCX_train"