ARSA_ML is a package for automated analysis of the Rashomon Set properties.
Project description
ARSA_ML - Automated Rashomon Set Analysis package
Weclome to the official ARSA_ML package site.
Overview
ARSA_ML is a Python library for detailed analysis of the Rashomon Sets - the collections of models that perform nearly equally well on a given dataset. It provides tools to create various objects, analyse the related properties and metrics, as well as visualize the results. The package is compatible with two AutoML frameworks - AutoGluon and H2O. Additionally, you may analyze your own set of models if you present their results in a requsted format (See : documentation).
Installation
Install the package with PyPI:
pip install arsa_ml
Example usage
from arsa_ml.pipelines.builder_abstract import *
from arsa_ml.pipelines.pipelines_user_input import *
#create pipeline from H2O saved models
builder = BuildRashomonH2O(models_directory=example_models_path,
test_data = test_h2o,
target_column=target_column,
df_name = 'heart',
base_metric='accuracy',
feature_imp_needed=True)
#preview Rashomon Set properties
builder.preview_rashomon()
#set epsilon value
builder.set_epsilon(0.03)
#launch pipeline
rashomon_set, visualizer = builder.build()
#close dashboard
builder.dashboard_close()
Documentation
For detailed package dokumentation visit documentation page
Authors
- Katarzyna Rogalska (repository owner)
- Zuzanna Sieńko
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