- Python 3.x
Clone the repository and install the dependencies,
git clone https://github.com/6ixGODD/ML-EnsembleHub.git
cd ML-EnsembleHub
pip install -r requirements.txt
Execute the script with command line options,
python main.py --data <path_to_data>
--cfg <path_to_config>
--save-dir <path_to_save_dir>
--name <name_of_experiment>
--save
--plot
in english:
--data
- specify the path to the data--cfg
- specify the path to the config--save-dir
- set the directory to save the results--name
- define the name of the experiment--save
- enable result saving (metrics, models)--plot
- enable plot
YAML configure the experiment:
shuffle: <bool>
random_state: <int>
preprocessing:
method: <method_name>/null
<method_name>:
<param_name>: <param_value>
classifiers:
method:
- <method1_name>
- <method2_name>
- ...
<method1_name>:
<param_name>: <param_value>
<method2_name>:
<param_name>: <param_value>
...
feature_selection:
method: <method_name>/null
<method_name>:
<param_name>: <param_value>
model_selection:
method: <method_name>
<method_name>:
<param_name>: <param_value>
shuffle
- shuffle the datarandom_state
- random statepreprocessing
- preprocessing method / disable(null)classifiers
- list of classifiersfeature_selection
- feature selection method / disable(null)model_selection
- model selection method
The data must be in the following format:
label | feature1 | feature2 | ... |
---|---|---|---|
0/1 | value1 | value2 | ... |
... | ... | ... | ... |
Execute the script with command line options,
python main.py --data data/credit.csv --cfg configs/credit.yml --save-dir output --name credit --save --plot
- metrics:
output/<name_of_experiment>/metrics/metrics.csv
- plots:
output/<name_of_experiment>/plots/
- models:
output/<name_of_experiment>/models/
- log:
output/<name_of_experiment>/log.txt
:)