Metadata-Version: 2.4
Name: nanodesclib
Version: 0.0.3
Summary: This is the library for descriptors calculation, data preprocessing and AutoML.
Home-page: https://github.com/NataliaPapina/nanodescriptors_library
Author: Natalia_Papina
Author-email: natalyapapina17@gmail.com
Project-URL: GitHub, https://github.com/NataliaPapina/nanodescriptors_library
Keywords: descriptors nanomaterials inorganic library nanodesclib
Classifier: Programming Language :: Python :: 3.11
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: optuna
Requires-Dist: shap
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: sklearn
Requires-Dist: xgboost
Requires-Dist: lightgbm
Requires-Dist: catboost
Requires-Dist: tqdm
Requires-Dist: warnings
Requires-Dist: pymatgen
Requires-Dist: re
Requires-Dist: itertools
Requires-Dist: collections
Requires-Dist: pathlib
Requires-Dist: functools
Requires-Dist: ast
Requires-Dist: json
Requires-Dist: yaml
Requires-Dist: typing
Requires-Dist: chemlib
Requires-Dist: pubchempy
Requires-Dist: inspect
Requires-Dist: thermo
Requires-Dist: rdkit
Requires-Dist: scipy
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NanoDescriptors is a Python library for automated descriptor generation, data preprocessing, and AutoML for nanomaterial property prediction (QSAR/QSPR).
Main features
Parses complex formulas (coreвЂ‘shell @, composites -//, nonвЂ‘stoichiometric, 19 material types)

Calculates >100 descriptors (electronic, thermodynamic, atomicвЂ‘mechanical, additive mixture descriptors)

Automatic data cleaning, encoding, skew correction, scaling

AutoML regression/classification with Optuna + SHAP/PLS/RFE feature selection + stacking ensembles
